Cannabis Consumption Used by Cancer Patients during Immunotherapy Correlates with Poor Clinical Outcome 3 The Laboratory of Cancer Biology and Cannabinoid Research, Department of Biology, Colorectal cancer is a major public health problem. Unfortunately, currently, no effective curative option exists for this type of malignancy. The most promising cancer treatment nowadays is immunotherapy which is also called biological or targeted therapy. This type of therapy boosts the patient’s immune system ability to fight the malignant tumor. However, cancer cells may become resistant to immunotherapy and escape immune surveillance by obtaining genetic alterations. Therefore, new treatment strategies are required. In the recent decade, several reports suggest the effectiveness of cannabinoids and Can-nabis sativa extracts for inhibiting cancer proliferation in vitro and in vivo, including in-testinal malignancies. Cannabinoids were shown to modulate the pathways involved in cell proliferation, angiogenesis, programmed cell death and metastasis. Because of that, they are proposed as adjunct therapy for many malignancies. By far less information exists on the potential of the use of cannabis in combination with immunotherapy. Here, we explore the possibility of the use of cannabinoids for modulation of immunotherapy of colon cancer and discuss possible advantages and limitations.
Cannabis Consumption Used by Cancer Patients during Immunotherapy Correlates with Poor Clinical Outcome
3 The Laboratory of Cancer Biology and Cannabinoid Research, Department of Biology, Technion-Israel Institute of Technology, Haifa 320003, Israel; [email protected] (S.C.-P.); [email protected] (G.M.L.); [email protected] (P.B.)
Gil M. Lewitus
3 The Laboratory of Cancer Biology and Cannabinoid Research, Department of Biology, Technion-Israel Institute of Technology, Haifa 320003, Israel; [email protected] (S.C.-P.); [email protected] (G.M.L.); [email protected] (P.B.)
2 Bruce Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa 320002, Israel; [email protected]
4 Statistic unit, Emek Medical Center, Afula 1834111, Israel; [email protected]
3 The Laboratory of Cancer Biology and Cannabinoid Research, Department of Biology, Technion-Israel Institute of Technology, Haifa 320003, Israel; [email protected] (S.C.-P.); [email protected] (G.M.L.); [email protected] (P.B.)
2 Bruce Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa 320002, Israel; [email protected]
Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Cannabis is widely used by patients with cancer to help with cancer symptoms and treatment side effects. Though cannabis has immunomodulatory effects, and its consumption among cancer patients needs to be carefully considered due to its potential effects on the immune system. In this report, we provide the first indication of the impact of cannabis consumption during immune checkpoint inhibitors (ICI) immunotherapy cancer treatment and show it may be associated with worsening clinical outcomes. Cancer patients using cannabis showed a significant decrease in time to tumor progression (TTP) and decreased overall survival (OS) compared to nonusers. In contrast, the use of cannabis reduced immune-related adverse events (iAE). Thus, our report constitutes the first warning sign to the use of cannabis as a palliative treatment in advanced cancer patients starting immunotherapy and suggests that its consumption should be used with attentiveness. Furthermore, we show that the levels of endogenous serum eCB and eCB-like lipids are affected by immunotherapy and may potentially constitute monitoring targets to cancer immunotherapy treatment, which currently has poor clinical markers for predicting patient response rates.
Cannabis or its derivatives are widely used by patients with cancer to help with cancer symptoms and treatment side effects. However, cannabis has potent immunomodulatory properties. To determine if cannabis consumption during immunotherapy affects therapy outcomes, we conducted a prospective observatory study including 102 (68 immunotherapy and 34 immunotherapy plus cannabis) consecutive patients with advanced cancers who initiated immunotherapy. Cannabis consumption correlated with a significant decrease in time to tumor progression and overall survival. On the other hand, the use of cannabis reduced therapy-related immune-related adverse events. We also tested the possibility that cannabis may affect the immune system or the tumor microenvironment through the alteration of the endocannabinoid system. We analyzed a panel of serum endocannabinoids (eCBs) and eCB-like lipids, measuring their levels before and after immunotherapy in both groups. Levels of serum eCBs and eCB-like lipids, before immunotherapy, showed no significant differences between cannabis users to nonusers. Nevertheless, the levels of four eCB and eCB-like compounds were associated with patients’ overall survival time. Collectively, cannabis consumption has considerable immunomodulatory effects, and its use among cancer patients needs to be carefully considered due to its potential effects on the immune system, especially during treatment with immunotherapy.
To date, the U.S. Drug Enforcement Administration (DEA) lists cannabis and its phytocannabinoids as Schedule I controlled substances that cannot be legally prescribed, possessed, or sold . Despite the lack of robust evidence, the use of cannabis as a palliative treatment to relieve the side effects of drugs used in a range of medical conditions has been approved or is under consideration in many countries around the world and assumed to be safe . Cannabis is particularly prevalent as a palliative treatment in oncology [2,3,4,5] to alleviate cancer symptoms, including nausea, anorexia, and cancer-related pain , despite the limited number of randomized clinical trials. Although the anti-inflammatory effects of cannabis and phytocannabinoids have long been known [7,8], the secondary effect of cannabis on the immune system has not yet been fully elucidated.
The biological activity of cannabis is mediated by modulation of the endocannabinoid system (eCBS). This system comprises of two G-protein-coupled receptors (GPCR), cannabinoid receptors type 1 and 2 (CB1 and CB2, respectively), the two endocannabinoids (eCBs) N-arachidonoyl ethanolamide (anandamide, AEA) and 2-arachidonoylglycerol (2-AG), and the enzymes responsible for the biosynthesis and hydrolytic inactivation of these eCBs . More recently, additional receptors, biosynthesizing and degrading enzymes, and eCB-like lipids have been recognized as part of an extended eCBS [10,11,12,13] or an “endocannabinoidome” . The extended eCBS, among other things, regulates immune responses in different cell types, affecting cytokine secretion, the induction of apoptosis, and immune cell activation in innate and adaptive immune responses . The classical eCB, AEA, can produce a dose-dependent inhibition of mitogen-induced T and B human lymphocyte proliferations . On the other hand, 2-AG has both pro- and anti-inflammatory effects. eCB-like lipids like the N-acyl ethanolamides: N-palmitoyl ethanolamide (PEA), N-oleoyl ethanolamide (OEA), and N-stearoyl ethanolamide (SEA) have been shown to inhibit both T-cell responses directly . Phytocannabinoids, the natural constituents of cannabis, also interact with the extended eCBS by activating and/or inhibiting eCB and eCB-related receptors, enzymes, and transporters [10,17]. For example, via inhibition of the cellular reuptake of AEA by most neutral phytocannabinoids or cannabidiol (CBD) inhibition of the hydrolyzing enzyme, fatty acid amide hydrolase (FAAH), which, in turn, is responsible for the degradation of AEA and other N-acyl ethanolamides [18,19]. Since cannabis is now widely used in oncology patients, it is of great importance to understand the effects of cannabis on the immune system and its possible interaction with immunotherapy, which is designed to artificially stimulate the immune system and improve the immune system’s natural ability to fight the disease.
Several studies show the effect of prolonged use of cannabis on the levels of eCBs. For example, Morgan et al.  observed a reduction of AEA levels in the cerebral spinal fluid (CSF), while an increase in 2-AG levels in the serum of chronic cannabis users. Furthermore, Leweke et al.  have shown that a two-week treatment with CBD increased circulating levels of AEA, PEA, and OEA in the serum of schizophrenia patients. In a recently published paper by our group , we also showed that different high-CBD cannabis extracts modulate the levels of eCB and eCB-like lipids in mouse brains and serum.
Immune checkpoint inhibitors (ICIs) target the molecule’s cytotoxic T-lymphocyte-associated protein 4 (CTLA4), programmed cell death protein 1 (PD-1) (also known as CD279PD-1), and programmed death-ligand 1 (PD-L1) (also known as CD274), either as a monotherapy or in combination with chemotherapy [23,24,25,26,27]. We previously showed in a retrospective observational study that cannabis use significantly reduces the response rates to nivolumab during immunotherapy treatment . In this prospective study, we aimed to evaluate the clinical outcome of cannabis use in patients initiating ICI therapy for advanced malignancies. In parallel, we systematically analyzed a comprehensive panel of serum eCB and eCB-like lipid levels to probe their possible variations as a result of cannabis consumption or immunotherapy treatment to test their potential effect on anticancer treatment or tumor progression. Given the immunomodulatory effects of eCB and eCB-like lipids, we hypothesized in this research that the effect of cannabis use on immunotherapy was possibly in part due to phytocannabinoids’ regulation of the endocannabinoidome. Although the majority of the studies investigated the “classical eCBs” (AEA and 2-AG), other eCB-like lipids have also been shown to regulate the immune system , supporting our motivation for analyzing these additional compounds.
2.1. Patient Characteristics
Between 01 September 2016 to 25 September 2018, a total of 102 cancer patients were included in this study. Recruitment included patients with metastatic malignancies (stage IV disease) initiating checkpoint inhibitor treatment: 34 patients used cannabis (cannabis-immunotherapy group: CI-G), and 68 did not use cannabis (immunotherapy group: I-G). About 70% of the patients were male, and more than 50% had non-small cell lung cancer (NSCLC) ( Table 1 ). Some differences between groups were unavoidable: liver metastasis of the immunotherapy group (I-G) (I-G 19%) vs. the immunotherapy-cannabis group (IC-G) (67%, p = 0.89), treatment type nivolumab and ipilimumab together (I-G 24% vs. IC-G 12% p = 0.15), line of treatment: 76% of patients in the IC-G were given immunotherapy as the second line of treatment vs. 54% in the I-G (odds = 1.40, p = 0.03) ( Table 1 ).
Demographics and medical conditions.
N = 68
N = 34
|Age in years median (range)||69 (18–92)||66 (37–85)|
|Female||22 (32.4)||10 (29.5)|
|Male||46 (67.6)||24 (70.5)||0.9399|
Eastern Cooperative Oncology Group
|1≤||55 (80.8)||24 (70.5)||0.3568|
|≥2||13 (19.1)||10 (29.4)||0.3568|
|Chronic diseases per patient—N (%)|
|22 (32.3)||13 (22.0)||0.7124|
|1||16 (23.5)||7 (20.5)||0.9332|
|2 or more||30 (44.1)||14 (41.1)||0.9437|
|Background diseases—N (%)|
|Chronic heart disease||18 (26.4)||5 (14.7)||0.2762|
|Diabetes||17 (25.0)||6 (17.6)||0.5576|
|High blood pressure||34 (50.0)||13 (34.1)||0.3612|
|Chronic obstructive pulmonary disease (COPD)||9 (13.2)||3 (8.8)||1|
|Hyperlipidemia||23 (33.8)||7 (20.5)||0.2491|
|Other||2 (2.9)||0 (0.0)||1|
|Type of malignancy—N (%)|
|Non-small cell lung cancer||37 (54.4)||20 (58.8)||0.8325|
|Melanoma||25 (36.7)||9 (26.4)||0.414|
|Renal cell carcinoma||4 (5.8)||2 (5.8)||1|
|Other||2 (2.9)||3 (8.8)||1|
|Main site of metastasis—N (%)|
|Brain||12 (17.6)||8 (13.2)||0.6593|
|Lungs||39 (57.3)||23 (67.6)||0.4303|
|Liver||13 (19.1)||11 (32.3)||0.2157|
|Immunotherapy given as—N (%)|
|First line of treatment||31 (45.5)||8 (23.5)||0.05178|
|Second line of treatment or more||37 (54.4)||26 (76.4)||0.05178|
|Checkpoint therapy—N (%)|
|Anti PD1: Pembrolizumab or Nivolumab||47 (69.1)||29 (85.2)||0.127|
|Ipilimumab and Nivolumab||16 (23.5)||4 (11.7)||0.2517|
|Anti PDL-1: Durvalumab or Atezolizumab||5 (7.3)||1 (2.9)||1|
Minor differences between groups of users vs. nonusers were found in liver or renal functions or the electrolytes balance before the initiation of the anticancer immunotherapy ( Table 2 ). Differences were also found in terms of the lymphocyte count at baseline (before immunotherapy), where 67% of cannabis users (IC-G group) showed low lymphocyte counts (without leukopenia) vs. 51% in non-cannabis users (I-G group) (one-tailed p = 0.08) ( Table 2 ). In other words, the users group had 16% more cases of low lymphocytes at baseline, which corresponds to a low-to-medium difference between groups (Cohen’s h = 0.31).
Abnormal laboratory tests before immunotherapy (according to local normal ranges).
n = 68
n = 34
|Lymphocytes ≤ 1.5 K/uL—N (%)||35 (51)||23 (67)||0.08|
|Blood count WBC ≤ 4.5 K/uL—N (%)||7 (10)||2 (6)||–|
|Alanine Aminotransferase (ALT) > 45||7 (10)||3 (9)||–|
|Aspartate Aminotrasferase (AST) > 35||8 (12)||5 (15)||–|
|Alkaline phosphatase level (ALKP) > 120||13 (19)||11 (32)||0.09|
|Renal Function—N (%)|
|Creatinine > 1.17 mL/min||12 (17)||3 (9)||–|
Among the cannabis users, most of the patients (71%) used the lowest prescribed monthly dose of cannabis (20 grams), and only ten patients used a dose of 30 or 40 grams before and during the immunotherapy treatment period. The use of cannabis had been started nine months to two weeks before the first immunotherapy treatment. The cannabis license in Israel in the years of the study includes only the monthly dose and the type of use, smoked or inhaled (cannabis flowers only), prepared cannabis oil, or combined use. Among the 32 cannabis users, eight used only cannabis oil, and six used combined oil and flowers. The patients had permission to change cannabis products monthly. The data of the different products used by the patients during the study period is limited.
2.2. Overall Response
The overall clinical outcomes were estimated in terms of complete response (CR), partial response (PR), and stable disease (SD) as to the Response Evaluation Criteria in Solid Tumors RECIST 1.1 criteria. Cannabis-users showed a significantly lower percentage of clinical benefit (CR + PR + SD) outcomes: 39% vs. 59% over nonusers (p = 0.035). CR and SD indexes were larger over nonusers, although the differences were not statistically significant (CR: I-G = 20% and IC-G = 9%, p = 0.1329, SD: I-G = 20% and IC-G = 9%, p = 0.13), and PR indexes were equivalent between groups (I-G = 19% and IC-G = 21%, p = 0.86). Cannabis users were more likely to show symptoms of progressive disease, namely: n = 29 out of n = 34 (61%) patients in the IC-G group compared to n = 27 patients out of n = 68 (41%) in the I-G experienced progressive disease (p = 0.035).
2.3. TTP and O.S.
The primary endpoint of the study was the time to tumor progression (TTP) (defined as the time from treatment initiation to time to tumor progression or death from any cause), with overall survival (OS) as a secondary endpoint (defined as the time from treatment initiation to death from any cause). These indexes were compared between cannabis users and nonusers (both groups undergoing immunotherapy treatment). Results show that the median TTP for cannabis-users (IC-G) was 3.4 months (95% CI, 1.8–6.0) vs. 13.1 months (95% CI, 6.0-NA) for nonusers (I-G) ( Figure 1 ). With a minimum follow-up of seven months, the median OS for cannabis use (IC-G) was 6.4 months (95% CI, 3.2–9.7) and 28.5 months (95% CI, 15.6-NA) for nonusers (I-G) (log-rank tests p = 0.0025 and p = 0.0009, respectively ( Figure 2 ). The analysis was conducted with an adjustment for the line of treatment, and we found a significant estimated hazard ratios of 1.95 (95% CI, 1.17–3.26) for TTP and 2.18 (95% CI, 1.241–3.819) for OS (p = 0.011 and p = 0.007), respectively. Overall, when compared to cannabis-users, nonusers were associated with more favorable TTP and OS outcomes.
Durability of time to tumor progression (TTP) among patients with advanced cancers receiving immunotherapy, comparing cannabis users to nonusers. Median TTP was 3.4 months (95% confidence interval (CI), 1.8–6.0) for cannabis users and 13.1 months (95% CI, 6.0–NA) for nonusers.
Durability of overall survival (OS) among patients with advanced cancers receiving immunotherapy. Kaplan-Meier estimates of OS among 102 patients divided into cannabis users and nonusers. OS is defined as the time to the last known alive date before the date of data analysis. Median OS was 6.4 months (95% confidence interval (CI), 3.2–9.7) for cannabis users and 28.5 months (95% CI, 15.6–NA) for nonusers.
2.4. Adverse Events
Adverse events (AEs) were documented during the entire study for both groups, including the most frequent side effects associated with the particular immunotherapy. Overall, cannabis-users reported a lower rate of treatment-related AEs compared with nonusers ( Table 3 ). The most frequent grade 2 and above immune-related AEs were skin toxicity (nine cases (13%) in the I-G vs. two (6%) in the IC-G), thyroid disorders (six cases (9%) of the I-G compared to two (6%) in the IC-G), and colitis (documented in six cases (9%) only in the nonuser group (I-G), p-value = 0.094). Additional immune-related AEs such as arthritis, adrenal-insufficiency, and pan-uveitis were reported in single patients and only in the nonuser group. One case of hepatitis was documented in each group. General deterioration and edema were reported in single patients in the cannabis-users group. Although the relation to immunotherapy was not completely defined, they were included as immune-related AEs; a steroids treatment was given, with some improvement. Overall, results indicated a significant reduction in immune-related AEs associated with the use of cannabis during immunotherapy (p = 0.057).
Reported immune-related adverse events (iAE), Common Terminology Criteria for Adverse Events (CTCAE) grade ≥ 2.
n = 68
n = 34
|Any iAE, grade ≥ 2—N (%)||28 (39)||7 (21)||0.057|
|Skin toxicity—N (%)||9 (13)||2 (6)||–|
|Colitis—N (%)||6 (9)||–|
|Thyroid disorders—N (%)||6 (9)||2 (6)||–|
|Other—N (%)||3 (4)||–|
|Arthritis—N (%)||1 (1.5)||–|
|Panuveitis—N (%)||1 (1.5)||–|
|Hepatitis—N (%)||1 (1.5)||1 (3)||–|
|General Deterioration—N (%)||1 (3)||–|
|Edema—N (%)||1 (3)||–|
2.5. eCB and eCB-Like Levels
To further test the possibility that a flow of ectopic Phytocannabinoids in the blood of cannabis users may modulate the eCBS and alter their levels, we analyzed a comprehensive panel of serum eCB and eCB-like lipids and measured their levels in cancer patients before and after immunotherapy from both cannabis users and nonusers. eCB and eCB-like serum concentrations were monitored in blood samples using a novel liquid chromatography-mass spectrometric (LC/MS) method recently developed and validated by our group  ( Table 4 ). Four lipids [N-eicosapentaenoyl ethanolamide (EPEA), O-arachidonoyl ethanolamide (O-AEA), N-arachidonoyl alanine (A-Ala), and N-arachidonoyl gamma-aminobutyric acid (A-GABA)] resulted below the detection limits in all patients and were excluded from this study. Blood samples taken from 36 patients before starting immunotherapy were analyzed for eCB and eCB-like serum levels: 19 patients from the nonusers group (I-G) and 17 from the cannabis-users group (IC-G) ( Table 4 ). Results indicate that (before immunotherapy) a single eCB-like lipid [i.e., 2-oleoyl glycerol (2-OG)] out of 28 was associated with significantly different levels between groups (p < 0.04), while all the other compounds showed no significant differences between groups, suggesting that cannabis consumption had no substantial and/or permanent effects on the observed eCB and eCB-like levels before immunotherapy initiation (Table 4 ).
Endocannabinoids serum concentration.
|Analyte (ng/mL)||before Immunotherapy
|n = 8||n = 6||n = 8||n = 6|
|Median (IQR)||Median (IQR)||Median (IQR)||Median (IQR)|
|LnA||432.52 (211.53, 522.96)||240.99 (228.69, 298.71)||184.35 (155.67, 365.81)||252.72 (118.91, 312.50)||0.443|
|AA||685.94 (449.35, 831.05)||627.04 (563.61, 700.79)||457.61 (412.89, 657.92)||564.63 (549.41, 583.55)||0.315|
|EPEA||0.00 (0.00, 0.00)||0.00 (0.00, 0.03)||0.00 (0.00, 0.00)||0.00 (0.00, 0.00)||–|
|LnEA||0.00 (0.00, 0.03)||0.00 (0.00, 0.00)||0.00 (0.00, 0.01)||0.01 (0.00, 0.03)||0.351|
|DHEA||0.34 (0.29, 0.40)||0.33 (0.28, 0.37)||0.29 (0.27, 0.34)||0.25 (0.22, 0.29)||0.41|
|AEA||0.31 (0.26, 0.41)||0.35 (0.29, 0.43)||0.32 (0.25, 0.35)||0.25 (0.20, 0.34)||0.559|
|LEA||0.36 (0.35, 0.48)||0.41 (0.33, 0.45)||0.36 (0.31, 0.39)||0.28 (0.24, 0.33)||0.745|
|PEA||0.17 (0.11, 0.21)||0.08 (0.04, 0.21)||0.11 (0.06, 0.21)||0.04 (0.01, 0.18)||0.45|
|OEA||0.35 (0.27, 0.38)||0.35 (0.31, 0.46)||0.31 (0.26, 0.39)||0.25 (0.19, 0.30)||0.412|
|SEA||0.13 (0.07, 0.24)||0.10 (0.03, 0.23)||0.10 (0.05, 0.17)||0.11 (0.02, 0.24)||0.335|
|DtEA||0.01 (0.01, 0.02)||0.02 (0.02, 0.03)||0.01 (0.00, 0.02)||0.02 (0.01, 0.03)||0.582|
|2-AG||3.27 (1.55, 5.12)||4.02 (2.80, 5.84)||2.18 (1.78, 3.78)||3.06 (2.70, 4.58)||0.472|
|2-LG||48.74 (33.36, 104.28)||44.91 (33.91, 71.57)||50.95 (35.25, 73.29)||73.83 (38.35, 100.75)||0.352|
|2-OG||71.84 (36.88, 134.98)||52.58 (38.89, 93.19)||71.59 (52.16, 95.28)||77.85 (57.94, 84.19)||0.338|
|A-Am||0.02 (0.02, 0.03)||0.02 (0.01, 0.02)||0.02 (0.01, 0.03)||0.01 (0.00, 0.01)||0.607|
|L-Am||4.65 (1.81, 15.28)||44.44 (15.32, 55.42)||52.71 (10.04, 63.00)||30.45 (9.10, 43.01)||0.625|
|O-Am||12.85 (7.11, 15.89)||6.68 (3.19, 19.69)||35.98 (19.39, 58.34)||13.85 (6.39, 23.43)||0.384|
|2-AGe||0.49 (0.46, 0.51)||0.41 (0.40, 0.45)||0.45 (0.41, 0.48)||0.44 (0.39, 0.50)||0.478|
|O-AEA||0.00 (0.00, 0.00)||0.00 (0.00, 0.00)||0.00 (0.00, 0.00)||0.00 (0.00, 0.00)||–|
|A-serine||0.22 (0.00, 0.23)||0.22 (0.22, 0.23)||0.23 (0.22, 0.23)||0.22 (0.22, 0.23)||0.647|
|DH-Gly||0.00 (0.00, 0.42)||0.00 (0.00, 0.00)||0.20 (0.00, 0.41)||0.00 (0.00, 0.00)||0.422|
|A-Gly||0.07 (0.00, 0.15)||0.07 (0.00, 0.14)||0.07 (0.00, 0.14)||0.00 (0.00, 0.10)||0.234|
|L-Gly||0.37 (0.33, 0.43)||0.26 (0.24, 0.31)||0.32 (0.28, 0.38)||0.26 (0.19, 0.37)||0.606|
|P-Gly||0.92 (0.82, 1.11)||0.90 (0.80, 1.15)||0.90 (0.79, 1.04)||0.78 (0.66, 1.04)||0.352|
|O-Gly||0.64 (0.49, 0.68)||0.49 (0.40, 0.65)||0.54 (0.41, 0.60)||0.31 (0.28, 0.51)||0.524|
|A-Ala||0.00 (0.00, 0.15)||0.00 (0.00, 0.00)||0.00 (0.00, 0.00)||0.00 (0.00, 0.00)||–|
|O-Ala||0.40 (0.35, 0.49)||0.36 (0.35, 0.36)||0.39 (0.31, 0.44)||0.34 (0.34, 0.37)||0.586|
|A-GABA||0.00 (0.00, 0.00)||0.00 (0.00, 0.00)||0.00 (0.00, 0.00)||0.00 (0.00, 0.00)||–|
Main descriptive statistics by groups, data = Median, interquartile range (IQR); SMD, standardized mean deviation between groups; LnA, linolenic acid; AA, arachidonic acid; EPEA, N-eicosapentaenoyl ethanolamide; LnEA, N-linolenoyl ethanolamide; DHEA, N-docosahexanoyl ethanolamide; AEA, N-arachidonoyl ethanolamide; LEA, N-linoleoyl ethanolamide; PEA, N-palmitoyl ethanolamide; OEA, N-oleoyl ethanolamide; SEA, N-stearoyl ethanolamide; DtEA, N-docsatetraenoyl ethanolamide; 2-AG, 2-arachidonoyl glycerol; 2-LG, 2-linoleoyl glycerol; 2-OG, 2-oleoyl glycerol; A-Am, N-arachidonoyl amide; L-Am, N-linoleoyl amide; O-Am, N-oleoyl amide; 2-AGe, 2-arachidonoyl glycerol ether; O-AEA, O-arachidonoyl ethanolamide; A-Ser, N-arachidonoyl serine; DH-Gly, N-docosahexaenoyl glycine; A-Gly, N-arachidonoyl glycine; L-Gly, N-linoleoyl glycine; P-Gly, N-palmitoyl glycine; O-Gly, N-oleoyl glycine; A-Ala, N-arachidonoyl alanine; O-Ala, N-oleoyl alanine; A-GABA, N-arachidonoyl gamma-aminobutyric acid.
Two-way analysis of endocannabinoid (eCB) and eCB-like lipids variance. Each panel represents a different compound where levels are expressed in (ng/mL) on the y-axis. Dots represent expected values, and lines represent standard error of the mean before and after immunotherapy (grey vs. orange bars) over cannabis users vs. nonusers.
Next, we tested whether eCB and eCB-like levels at the baseline (before immunotherapy) were likely to be associated with any significant variation of OS ( Figure 4 ). Four lipids correlated with OS time; in particular, SEA, 2-AG, and 2-linoleoyl glycerol (2-LG) showed an inverse association with OS expectations (the higher the concentrations of these compounds, the lower the OS). On the other hand, increasing levels of N-arachidonoyl amide (A-Am) were associated with increasing OS expectations ( Figure 4 ). The baseline levels of all the remaining compounds were not associated with significant variations of OS in both MC-user and nonuser groups.
Correlation between eCB concentrations (ng/mL) and overall survival time (OS) measured at time zero (before immunotherapy initiation). Each panel represents a different eCB. Each data point represents a patient with the corresponding anonymized identification number. The blue line indicates the linear trend across the data points. The trends were fitted by means of linear regressions with Gaussian kernel. N-arachidonoyl amide (A-Am) includes two extreme values that were considered feasible measurements to be included. The shaded areas indicate a 95% confidence interval of the OS trend. Nonshaded segments indicate that the confidence interval was outside the limits of the y-axis. R2/R2 adjusted parameters are, respectively: N-stearoyl ethanolamide (SEA) = 0.220/0.196, 2-arachidonoylglycerol (2-AG) = 0.139/0.110, 2-linoleoyl glycerol (2-LG) = 0.110/0.080, and A-Am = 0.234/0.211. Estimated p-values for the slopes were, respectively: SEA = 0.005, 2-AG = 0.036, 2-LG = 0.064, and A-Am = 0.003. All slopes’ estimate p-values were significant at a 0.1 level, indicating significant variations in OS-time per unit change of patients’ serum eCB concentrations at the baseline.
Despite the growing number of cannabis studies showing its efficacy as palliative therapy, its overall effects on the eCBS or the immune systems are mostly overlooked. Nonetheless, the properties of cannabis as a potent anti-inflammatory, immunomodulatory, and immune suppressor are well-known but never before considered in the context of immunotherapy. In this prospective observatory clinical study, we examined the link between cancer immunotherapy and its possible interaction with cannabis. We aimed to better understand the consequences of cannabis consumption during the ICI immunotherapy of patients with advanced cancers.
Considering that the random assignment of patients simply to “cannabis-users” is highly problematic, we designed a prospective study based on real-life medical records. Primarily, we note that, with this given study design, when differences between treatment groups (cannabis-users vs. nonusers) are inevitable, the effect of cannabis consumption is delimited. We minimized potential biases by making the treatment groups (cannabis-users vs. nonusers) comparable concerning the control variables at enrollment time. In that context, we prioritized the matching of clinical parameters rather than medical treatment history.
In view of the intrinsic limitations of this type of study, and in light of no other prior clinical indications to the subject, our results indicated that cannabis consumption should be carefully considered in patients with advanced malignancies treated with immunotherapy. Our data suggest that exposure to cannabis before or during ICI immunotherapy may associate with worsening success rates. These observations were in-line with our previous retrospective observational study, where cannabis-users were associated with reduced response rates to nivolumab . Indeed, in this current study, our data indicate that cannabis-users were associated with shorter TTP and shorter OS ( Figure 1 and Figure 2 ). Furthermore, lymphocyte counts at the baseline were lower in the cannabis-users group ( Table 2 ), where higher counts correlated positively with the treatment success rate. Remarkably, in the current analysis, cannabis users were also associated with a lower number of immune-mediated iAEs. Of note, it has been shown that patients with advanced melanoma, renal cell carcinoma, or non–small cell lung cancer treated with nivolumab, who developed treatment-related iAEs, were likely to result in significantly prolonged five-year OS . Incidentally, the immunosuppressive effect of cannabis has been highlighted in such a way that clinical tests with selective agonists of cannabinoid receptors (CB1 and CB2) are being evaluated as a new class of immunosuppressive and anti-inflammatory therapeutic targets for autoimmune diseases when the dampening of the immune system is beneficial .
Cannabinoids and, particularly, various phytocannabinoids have been shown to affect the functional activities of immune cells [7,30,31,32,33,34], while the inhibitory effect of cannabis on lymphocytes has been widely observed before . For example, phytocannabinoids have the potential to modulate the activation and balance of human T-helper 1 (Th1)/T-helper 2 (Th2) cells, lymphocytes, and killer cells [36,37]. Phytocannabinoids and, particularly, (-)-Δ 9 –trans-tetrahydrocannabinol (Δ 9 -THC) were found to suppress the ability of T-cells to respond to those mitogen-stimulated [37,38,39]. Importantly, Δ 9 -THC was also shown to differentially suppress CD8 T-cells and cytotoxic T lymphocytes (CTLs) and reduce their cytolytic activity  or may trigger T cell exhaustion [41,42]. Additionally, Δ 9 -THC inhibits both the proliferation of lymphocytes responding to an allogeneic stimulus and the maturation of these lymphocytes to mature CTLs . All of the above have the potential to interfere with anticancer biological immunotherapy and were, therefore, our motivation to analyze it in a prospective comparative clinical study currently ongoing in our labs.
We also tested the possibility that cannabis affects the immune system or the tumor microenvironment through the alteration of patients endogenous eCB and eCB-like lipid levels as a result of the addition of exogenous phytocannabinoids (due to cannabis consumption). We systematically analyzed a comprehensive panel of serum eCB and eCB-like lipids measured on cancer patients before and after immunotherapy from both groups. Surprisingly their baseline serum levels, before immunotherapy, showed no significant differences between groups. After immunotherapy, only nine eCB and eCB-like levels showed considerable variations (equally in both groups of cannabis-users and nonusers), while others remained invariant concerning the pre-immunotherapy levels ( Figure 3 ). Collectively, our data imply that eCB and eCB-like levels appear to be affected mostly by immunotherapy rather than by cannabis consumption. Nonetheless, even though phytocannabinoids do not directly alter eCB and eCB-like lipid serum levels, we found an association between the treatment success rate of four of these compounds independently from cannabis exposure ( Figure 4 ), suggesting that the effect of eCB and eCB-like lipids on immunotherapy success rates should be further examined.
Overall, our current study, with its limitations, demonstrates a statistically significant interaction between cannabis exposure before and during the ICI immunotherapy of advanced malignancies, their lymphocytes counts, and the detected immunotherapy success rates.
Patients were recruited consecutively between 1 September 2016 and 25 September 2018. The study took place in the Division of Oncology at Rambam Health Care Campus, Haifa, Israel and was approved by the institutional ethics committee (Certificate 0089-16-RMB). The selection of suitable candidates for the study was conducted through the hospital’s computerized system. Inclusion criteria were patients over 18 years of age and diagnosed stage IV cancer. All patients were recruited during the initiation of checkpoint inhibitor treatment, including anti-PD-1 (Pembrolizumab or Nivolumab), anti-PD-L1 (Durvalumab or Atezolizumab), or combined anti-PD-1 and anti-CTLA4 (Ipilimumab and Nivolumab). All patients gave written informed consent for the prospective evaluation of their medical data and blood samples taken before immunotherapy initiation and after 11–14 weeks of treatment. Data on demographics and medical history was extracted from the medical files. This data included age, type of cancer, stage (according to the American Joint Committee on Cancer, seventh edition), diagnosis date, smoking status, metastases location, treatment line number, immunotherapy details, and cannabis start date.
4.2. Assessments and Analyses
Patients were followed prospectively for tumor responses as evaluated using the RECIST criteria based on imaging assessments carried out every 11–14 weeks. Time to tumor progression (TTP) was calculated as the time from study enrollment until the tumor worsens, spreads, or death (whichever occurred first). Overall survival (OS) was calculated as the time from study enrollment until death from any cause. Only patients who started using cannabis before the initiation of checkpoint inhibitor treatment were included in the cannabis user group. In total, 102 patients were included in this study: 34 patients used cannabis (cannabis-immunotherapy group: CI-G), and 68 did not use cannabis (immunotherapy group: I-G).
Adverse events (AE) and immune-related AE (iAE) were assessed using the National Cancer Institute Common Terminology Criteria for Adverse Events, version 4.03.32. Adverse events were evaluated throughout the study while participants received treatment and until 90 days after study completion .
4.4. Statistical Analysis
Sample size calculation: We previously reported in a retrospective study that patients with advanced malignancies initiating immunotherapy treatment had a 14% combined (cannabis user and nonuser) rate of complete response (CR) and a 30% rate of partial response (PR) . Accordingly, we calculated that this prospective study required 243 patients (with a group allocation ratio of 1:2, i.e., 81 vs. 162 participants, respectively) to achieve the same difference, with a power of 80% and an alpha of 5% for the two-tailed test. We hypothesized that such difference, with a larger sample size, may translate to significant differences in the TTP. We planned an interim analysis after recruitment of at least 40% of the patients, including a minimum of 30 patients in the cannabis user group, to test our estimation. Patient recruitment was terminated after the interim analysis of 102 patients (n = 34 users and n = 68 nonusers). A subset of users and nonusers was tested for serum levels before and after therapy initiation.
A series of χ 2 tests or Fisher’s exact tests (when the assumptions of the parametric χ 2 test were not met) and nonparametric Mann–Whitney U tests were conducted to analyze the differences between patients’ characteristics in both groups. Time to tumor progression (TTP) and overall survival (OS) was estimated using the Kaplan-Meier survival curve by group, and the log-rank test was computed to differentiate the survival curves between groups. Hazard ratios and the corresponding 95% CIs based on a Cox proportional hazards regression model were provided for multivariate analyses. We computed 2-tailed p-values, where p < 0.05 was considered a statistically significant result. Statistical analyses were performed using the SAS software package version 9.4 (SAS Institute, Cary, NC, USA).
We used a nonparametric two-way analysis of variance (namely, The Scheirer–Ray–Hare test, SRH) to test the impact of cannabis consumption on immunotherapy, as well as their potential effects on eCB levels. In addition, we used linear regression to summarize the relationship between eCB levels and OS time. Statistical analysis was performed using R statistical software (R Foundation for Statistical Computing, Vienna, Austria) and the dedicated libraries Tidyverse, Tableone, and Stats.
4.5. Measurement of eCB Serum Levels
Analysis of eCB and eCB-like lipids was performed according to a method recently developed and validated by our group . Briefly, liquid chromatography-mass spectrometric (LC/MS) grade acetonitrile, methanol, and water for the mobile phase and high-performance liquid chromatography (HPLC) grade methanol, acetonitrile, and water for sample preparation were obtained from Mercury Scientific and Industrial Products Ltd. (Rosh Haayin, Israel). LC/MS grade acetic acid was purchased from Sigma-Aldrich (Rehovot, Israel). All the standards were of analytical grade (>98%). LnA, AA, EPEA, 2-AG, AEA, and N-linoleoyl amide (L-Am) were purchased from Sigma-Aldrich (Rehovot, Israel). All other standards and deuterated internal standards (d-ISs), including: N-linolenoyl ethanolamide (LnEA), N-docosahexanoyl ethanolamide (DHEA), LEA, PEA, OEA, SEA, DtEA, 2-LG, 2-OG, A-Am, O-Am, 2-arachidonoyl glycerol ether (2-AGe), O-AEA, N-arachidonoyl serine (A-Ser), N-docosahexaenoyl glycine (DH-Gly), N-arachidonoyl glycine (A-Gly), N-linoleoyl glycine (L-Gly), N-palmitoyl glycine (P-Gly), N-oleoyl glycine (O-Gly), A-Ala, N-oleoyl alanine (O-Ala) and A-GABA, AA-d8, DHEA-d4, AEA-d4, LEA-d4, PEA-d4, OEA-d4, SEA-d5, 2-AG-d5, A-Ser-d8, and A-Gly-d8, were purchased from Cayman Chemical (Ann Arbor, MI, USA). Six-hundred microliters of the extraction solution (methanol:acetonitrile:acetic acid in a ratio 50:50:0.1) spiked with 20 ng/mL d-ISs were added to 200 µL serum samples. Samples were thoroughly vortexed and centrifuged at 14,000 rpm and 4 ℃ for 20 min to precipitate proteins and cells. The supernatants were then transferred into 3 mL of 0.1% v/v acetic acid in water and loaded onto preconditioned Agela Cleanert C8 solid-phase extraction (SPE) cartridges (500 mg of sorbent, 50-μm particle size). eCB and eCB-like lipids were eluted from the columns using 2 mL of 0.1% v/v acetic acid in methanol, evaporated to dryness by speed vac, reconstituted in 100-µl ethanol, and filtered through a 0.22-µm polytetrafluoroethylene (PTFE) syringe filter for LC/MS analysis. Quantification of eCB and eCB-like lipids was performed using a Thermo Scientific ultra-high-performance liquid chromatography (UHPLC) system coupled with a Q Exactive™ Focus Hybrid Quadrupole-Orbitrap MS (Thermo Scientific, Bremen, Germany). The chromatographic separation was achieved using a Halo C18 Fused Core column (2.7 μm, 150 mm × 2.1 mm internal diameter) with a guard column (2.7 μm, 5 mm × 2.1 mm i.d.) (Advanced Materials Technology, Wilmington, DE, USA) and a ternary A/B/C multistep gradient (solvent A: 0.1% acetic acid in Milli Q water, solvent B: 0.1% acetic acid in acetonitrile, and solvent C: methanol; all solvents were of LC/MS grade). The multistep gradient program was established as follows: initial conditions were 50% B raised to 67% B until 3 min, held at 67% B for 5 min, and then increased to 90% B until 12 min, held at 90% B until 15 min, decreased to 50% B over the next min, and held at 50% B until 20 min for re-equilibration of the system prior to the next injection. Solvent C was initially 5% and then lowered to 3% until 3 min, held at 3% until 8 min, raised to 5% until 12 min, and then kept constant at 5% throughout the run. A flow rate of 0.25 mL/min was used, the column temperature was 30 °C, and the injection volume was 1 μL. MS acquisition was carried out with a heated electrospray ionization (HESI-II) ion source operated in switching mode. Source parameters were as follows: sheath gas flow rate, auxiliary gas flow rate, and sweep gas flow rate: 50, 20, and 0 arbitrary units, respectively; capillary temperature: 350 °C; heater temperature: 50 °C; and spray voltage: 3.00 kV. The scan range was 150–750 m/z for all acquisition events. MS was operated in full MS 1 mode at 70,000 resolution, and the AGC target was set to 10 6 with a maximum injection time of 100 ms.
The absolute quantification of eCB and eCB-like lipids was performed by the stable isotope dilution method. Ten-point standard mixes of the analytical standards were prepared in ethanol and spiked with a mixture of all d-ISs at a concentration of 30 ng/mL to yield a calibration range of 0.1 to 1000 ng/mL for all compounds. The ratios of the unlabeled and labeled ions were plotted against the amounts of spiked standards, and the calibration curves were determined empirically according to the weighted least-squares linear regression method, with a weighting factor of 1/X. Since 2-monoacylglycerols (MAGs) spontaneously undergo isomerization to biologically inactive 1-MAGs through the migration of the acyl group from the sn-2 to sn-1/3 position, we summed, in this study, the peaks of 1- and 2-MAGs (total MAGs), as previously suggested in the literature [44,45].
5. Conclusions and Study Limitations
The findings of our current prospective observational report recognize the technical limitations of the study design and, so far, lack a mechanism to support the hypothesis presented and should be evaluated in light of the limitations. The study includes a relatively small group of patients in the main clinical categories, such as different cancer types and diverse lines of oncology treatment. Those differences lead to high heterogeneity in the study population. On the other hand, the patients were recruited consecutively, strengthening the daily clinical aspects of the findings, and still, no statistically significant differences were found in the baseline demographic and clinical variables between the study groups, except to the line of treatment that was corrected statistically for the survival analysis. However, other specific characteristics of the tumor, the patient, or the type of immunotherapy treatment made have influences that were not evaluated well due to the sample size. Another significant limitation is the data collected regarding the use of cannabis. All cannabis users included in the study used less than 40 g of cannabis monthly. This amount, according to the Israeli Health Office, is still considered a low amount. However, as mentioned before, in the period of the study, most patients changed cannabis products between months according to cannabis companies recommendations and not medical ones. This aspect of the study prevents homogeneous data regarding the different influences on the immune system that may exist between the various cannabis products.
Nonetheless, we provide here the first indication of the effect of cannabis consumption during ICI immunotherapy treatment and show it may be associated with worsening clinical outcomes when compared to nonusers. Thus, our report constitutes the first warning sign to the use of cannabis as a palliative treatment in advanced cancer patients starting immunotherapy and suggest that its consumption should be carefully considered.
Additionally, our study shows that, while cannabis consumption does not alter the endogenous levels of serum eCB and eCB-like lipids, their levels appear to be affected by immunotherapy. This may provide monitoring opportunities and potential targets of pharmacological interest to cancer immunotherapy treatment, which currently has poor clinical markers for predicting patient response rates, which remain around 20–35%. Our study provides another demonstration of the fact that cannabis exposure may strongly impact the immune system, and its adverse effects on immunotherapy outcomes should be further tested. It should be noted, however, that eCB and several eCB-like lipids are biosynthesized and metabolized locally and rapidly and are affected by many different factors. Therefore, circulating eCBs often do not represent local disturbances to the eCB tone, and their concentrations are not necessarily related to the microenvironment of the tumor. Additionally, in this study, we could not provide eCB analyses before the cannabis treatment.
The authors would like to thank all patients, families, and caregivers who participated in the study.
|CB1 and CB2, respectively||Cannabinoid receptors type 1 and 2|
|ICIs||Immune Checkpoint Inhibitors|
|CTLA4||Cytotoxic T-lymphocyte-associated protein 4|
|PD-1||Programmed cell death protein 1|
|PD-L1||Programmed Death-ligand 1|
|NSCLC||Non-Small Cell Lung Cancer|
|DEA||Drug Enforcement Administration|
|TTP||Time to tumor progression|
|CTLs||Cytotoxic T Lymphocytes|
G.B.-S. and D.M. conceived and designed the project; I.C., A.J., and S.C.-P. collected and analyzed the endocannabinoids data and conducted all statistical analyses; G.M.L., L.O.-A., P.B., and D.M. measured the circulating levels of the serum eCB and eCB-like lipids; A.P., I.T., O.V., M.W., M.M., and G.B.-S. participated in the collection of the clinical data; and I.C., G.B.-S., D.M., and G.M.L. wrote the paper. All authors have read and agreed to the published version of the manuscript.
Cohen Idan was supported by the Israeli Cancer Association (ICA) (grant number 20200021) and the Israel Ministry of Health grant, together with Gil Bar-Sela (grant number 3000015198). David Meiri was supported in part by the Evelyn Gruss Lipper Charitable Foundation (2027093) and the Israeli Ministry of Agriculture and Rural Development.
Conflicts of Interest
The authors declare no conflict of interest.
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Articles from Cancers are provided here courtesy of Multidisciplinary Digital Publishing Institute (MDPI)
Cannabinoids, Medical Cannabis, and Colorectal Cancer Immunotherapy
Colorectal cancer is a major public health problem. Unfortunately, currently, no effective curative option exists for this type of malignancy. The most promising cancer treatment nowadays is immunotherapy which is also called biological or targeted therapy. This type of therapy boosts the patient’s immune system ability to fight the malignant tumor. However, cancer cells may become resistant to immunotherapy and escape immune surveillance by obtaining genetic alterations. Therefore, new treatment strategies are required. In the recent decade, several reports suggest the effectiveness of cannabinoids and Cannabis sativa extracts for inhibiting cancer proliferation in vitro and in vivo, including intestinal malignancies. Cannabinoids were shown to modulate the pathways involved in cell proliferation, angiogenesis, programmed cell death and metastasis. Because of that, they are proposed as adjunct therapy for many malignancies. By far less information exists on the potential of the use of cannabis in combination with immunotherapy. Here, we explore the possibility of the use of cannabinoids for modulation of immunotherapy of colon cancer and discuss possible advantages and limitations.
Nowadays, colorectal cancer (CRC) is considered to be the third most deadly and the fourth most commonly detected cancer in the world (1). Despite the presence of highly advanced screening techniques, the incidence rate has been steadily increasing globally (2). It is estimated that the global burden of colorectal cancer is expected to rise by 60% to more than 2.2 million newly diagnosed cases and 1.1 million deaths by 2030 (3). Factors, like sedentary lifestyle, increased consumption of alcohol, tobacco, red meat, genetic predisposition, chronic inflammatory processes of the gastrointestinal tract, are triggering factors of this type of malignancy (4). Adenomatous polyps are known to be the main precursors of CRC. The transformation rate of these polyps into carcinoma is ~0.25% per year. When these lesions have a high grade of dysplasia and villous architecture, the risk of being transformed into malignancy rises to 50% (5).
Understanding the pathogenesis of colorectal cancer is very important for choosing the right therapy. Etiology of CRC is complex and includes the accumulation of acquired epigenetic and genetic modifications that transform normal epithelial cells into malignant ones. The classical tumor progression model is called the development of the polyp- carcinoma sequence which involves three main steps. The first step is the formation of benign neoplasms like adenomas and sessile serrated polyps. The second step is characterized by the progression of benign tumors into more histologically advanced neoplasms, and the last step -their transformation into carcinoma. This process might take many years without showing any signs and symptoms. When CRC has developed, it still might take several years before it is diagnosed. CRC is caused by mutations in oncogenes, tumor suppressor genes, and genes involved in DNA repair mechanisms. One of the first mutations typically occurs in adenomatous polyposis coli (APC), a tumor suppressor gene, followed by mutations in KRAS, TGF-β, BAX, BRAF, and other genes (6).
Most cases of CRC are sporadic (70–80%), while the inherited and familial CRC cases account for roughly 5 and 25%, respectively. Sporadic cancers arise due to point mutations, and the molecular pathogenesis of these cancers is very heterogeneous in nature. The inherited group of this particular malignancy is due to the inherited mutations and can be subdivided into two groups: polyposis and non-polyposis. The polyposis type includes mostly familial adenomatous polyposis which is characterized by the presence of numerous possibly malignant polyps in the colon. The non-polyposis variant is represented by Lynch syndrome (7). The familial CRC is also due to the inherited mutations, and it runs in the families without the presence of particular inherited syndromes (8).
Recently, two molecular pathological classifications have been proposed based on the broad-range genomic and transcriptomic analysis of CRC. The first one is called The Cancer Genome Atlas (TCGA) that has three groups: hypermutated (13%), ultramutated (3%), and chromosomal instability (84%). The hypermutated category is characterized by a high mutation rate, defective mismatch repair (dMMR) with a good prognosis, but poor prognosis after relapse. The ultramutated type has an extremely high mutation rate with DNA polymerase epsilon proofreading mutation and generally good prognosis. The majority of CRC are distinguished by chromosomal instability (CIN) with features of a low mutation rate but a high frequency of DNA somatic copy number alterations. The second gene expression-based classification is called Consensus Molecular Subtypes (CMS) that has four groups. CMS1 (14%) is characterized by microsatellite instability (MSI), BRAF oncogene mutation and a vigorous immune activation. The poor survival rate after recurrence has been noticed in patients with this subtype. CMS2 (37%), also called canonical, exhibits a high chromosomal instability and activation of WNT and MYC signaling. CMS3 (13%), known as metabolic, has numerous KRAS mutations and deregulated pathways of metabolism. CMS4 (23%), called mesenchymal, is described by the presence of stromal infiltration, the highly expressed mesenchymal genes, the activation of transforming growth factor-beta, a worse overall and relapse-free survival compared to patients from other groups (7, 9). These classifications have provided information about a proper treatment selection and patients’ prognosis, thus being very important for ongoing and future clinical trials.
The main therapeutic options available nowadays for patients with CRC are surgery, chemotherapy, immunotherapy, radiotherapy. The 5-year survival rate of patients with early stages of CRC is almost 90%. Due to subtle symptoms, more than half of patients are diagnosed when they have already developed advanced malignancies. The 5-year survival rate is only 10% or less when patients have metastases (10).
Among new potential therapeutic approaches, treatment with cannabinoids and Cannabis sativa extracts have been shown to be efficient in inhibiting cancer growth in vitro and in vivo (11). C. sativa plant contains phytocannabinoids, terpenoids, flavonoids, fatty acids and other molecules. Cannabinoids act through the endocannabinoid system which is composed of receptors like cannabinoid 1 (CB1), cannabinoid 2 (CB2), transient receptor potential channels of the vanilloid subtype 1 and 2 (TRPV1, TRPV2), G protein-coupled receptors 18, 55, 119 (GPR18, GPR55, GPR119), endocannabinoids such as 2-arachidonoylglycerol and anandamide (2-AG, AEA), and enzymes responsible for their metabolism. The main biosynthetic emnzymes are NAPE-phospholipase D (NAPE-PLD) and diacylglycerol lipase (DAGL); the main degradation enzymes are fatty acid amide hydrolase (FAAH) and monoacylglycerol lipase (MAGL). The main function of the endocannabinoid system is to maintain homeostasis (12). The CB1 receptor is mainly expressed in CNS, and the CB2 receptor, being the most prevalent in the immune system, is mostly present in peripheral organs. Both receptors are G-protein-coupled cell surface receptors that are coupled to the adenylyl cyclase and cAMP-protein kinase A pathways and the MAPK and PI3K pathways (13).
The Importance of the Immune System in CRC
In the past, tumors were defined as just a collection of homogeneous cancer cells. The aggressiveness of neoplasia has been described by its clinicopathological features. Recent progress in immunology and molecular biology has allowed us to become more familiar with the fundamental mechanisms of metastatic potential of tumors. Many studies in this field have broaden the knowledge and emphasized the importance of the immune system in the regulation of cancer growth. The main players of this process are innate immune cells like neutrophils, macrophages, mast cells, eosinophils, myeloid-derived suppressor cells (MDSCs), and adaptive immune cells such as T and B lymphocytes (14, 15).
Over the past decade, the knowledge of tumor microenvironment (TME) has become a key for understanding complex multistep tumorigenesis and developing novel treatment regimens and drugs (16). The cancer microenvironment includes resident and non-resident cells that are interconnected by different mediators, and each of them have a specific function. The communication between these cells and tumor cells within their surroundings essentially regulates the destiny of tumor progression. Immune cells can either inhibit or favor tumor growth (Table 1). New preclinical research has shown that non-antigen-presenting atypical cells are first targeted by the innate immune system; then, the inflammatory response promotes the formation of new blood vessels and the proliferation of tumor cells. Unfortunately, tumors can turn on the immunosuppressive mechanisms and escape the host immunosurveillance. The adaptive immune response needs the identification of non-self-antigens by the communication between proteins and the major histocompatibility complex of antigen-presenting cells and the receptors of CD8+ and CD4+ T cells through antigen presentation. Tumors might lose their antigenicity due to acquired faults in the antigen presentation, or they might be identified as self (25–27).
Table 1. Pro-tumorigenic and anti-tumorigenic effects of immune cells.
There are three phases of tumor immunoediting: elimination, equilibrium, and escape (Figure 1). During the first stage, immune cells eliminate the neoplastic cells that express surface proteins. Through the equilibrium phase, some cells persist as a result of their potential to camouflage surface molecules or by suppressing macrophages and T cells via the expression of substances like PD-1/2 on the antigen-presenting cells. In the last phase, some cells can escape from being killed, and this subsequently leads to evasion and proliferation of resistant clones. In addition, the degradation of the extracellular matrix by matrix metalloproteinases and new blood vessels formed as a result of abnormal angiogenesis promotes the formation of metastases (15).
Figure 1. Phases of immunoediting in colorectal cancer. Elimination includes the removal of neoplastic cells, equilibrium describes the survival of a fraction of transformed cells, and escape describes the evasion and proliferation of these cells.
As to the expression of cannabinoid receptors in the cells of the immune system, it has been demonstrated that the receptors are expressed in both adaptive and innate immunity. For example, CB1, CB2, and GPR55 receptors are expressed on the NK cells, CB1, CB2 – on the mast cells, T lymphocytes – on the B cells. Therefore, it can be hypothesized that phytocannabinoids can influence the function of the immune system, regulate inflammation and possess antitumor effects, etc (28).
The Role of Inflammation in Colorectal Carcinogenesis
Inflammation plays a crucial role in colorectal carcinogenesis, and it is considered nowadays as one of the emerging hallmarks of cancer (29). A better understanding of CRC and inflammation can lead to the development of new tumor biomarkers and more personalized and effective therapies. It is well-known that patients who suffer from chronic conditions such as inflammatory bowel disease have a much higher risk of developing CRC (30). Inflammation is considered an important driving force of colitis-associated CRC cancers, while its role in sporadic and hereditary cancers is less clear. The evidence demonstrates that non-steroidal anti-inflammatory drugs may prevent or postpone the CRC development (31). A meta-analysis of randomized trials showed that during follow-up after 20 years of using aspirin for 5 years, the mortality and incidence rate of CRC would be reduced by 30–40% (32).
Based on the CMS classification of CRC, CMS1, and CMS4 are considered inflammatory, with the former having a poor prognosis after relapse, and the latter—having the worst survival rate. In general, inflammation plays a dual role in the neoplasia. Targeting malignant cells by cytotoxic T lymphocytes or diminishing the non-specific inflammation by T-regs can lead to an anti-tumorigenic response. This type of response is called protective and is associated with Th1 polarization and a lower recurrence of CRC. The Th1 subtype produces IFN-γ and enhances the cell-mediated toxicity, while the Th2 subtype releases IL-4 and enhances a humoral B cell response. The most common pro-inflammatory cytokines are TNF-α, IL-6, IL-12, IL-2, and the most common anti-inflammatory ones are IL-10, IL-4, IL-5, TGF-β, and IFN-α (Table 2). The cells of the innate and adaptive immunity and other cells such as fibroblasts, mesenchymal cells and pericytes are important in the cancer-associated inflammation (57). The communication between these cells happens via a web of cytokines produced and secreted by immune cells after being stimulated. The role of theIL-10 signaling pathway remains controversial in CRC. A higher level of IL-10 is linked to a worse patients’ survival, while studies on animals show that it has a protective role by suppressing inflammation (46, 47). IL-6 is an activator of the STAT-3 signaling pathway and is often found in CRC patients; and it is also linked to a worse survival and increased risk of relapse (37, 57, 58). The stromal fibroblasts, obtained from colon cancer, produced prominent amounts of IL-6. The last one induced tumor angiogenesis by enhancing VEGF production (38). IL-6 facilitates the metastatic colonization of colorectal cancer cells. In IL6-/- mice the metastasis of CT26 cells into the liver were reduced and the function of CD8+ T cells was improved in vivo. Moreover, IL-6 deficient mice responded to anti-PD-L1 injection effectively by suppression of metastatic colonization, while this effect was not observed in IL6+/+ mice (39). IFN-γ is produced by CD4+, CD8+, and NK cells, and it induces apoptosis of cells. A loss of one copy of this interferon in Apcmin/+ mice showed a much faster progression to colon adenocarcinoma. CRC cells can minimize the anti-tumorigenic effects of interferon signaling by the type I interferon receptor chain that leads to a poor response to anti-PD1 checkpoint inhibitors (44). The expression of TNF-α is much higher in colorectal cancer than in adjacent normal colorectal tissue. The increased expression of this cytokine strongly correlates with the more advanced tumors (59). After TNF-α stimulation, was noticed increase in Metastasis-Associated in Colon Cancer 1 (MACC1) oncogene at both mRNA and protein levels. MACC1 induces cancer cell proliferation, survival and metastasis. The expession levels of this oncogene was reduced by knocking down the p65 NF-kB. In addition, the induction of MACC1, was hindered by monoclonal anti-TNF- α antibody, adalimumab (34). TNF- α increased levels of pro-inflammatory cytokines, such as IL-6 and IL-8 in vitro on HT-29 colorectal cancer cells (35). Another study showed that the effect of peptide vaccine, AH1, on CT26 colon tumor-bearing mice caused a modest inhibition of tumor growth, but the combination with F8-TNF increased the anticancer activity drastically. F8-TNF is an antibody fusion protein which delivers TNF to the tumor extracellular matrix. The synergism between the peptide vaccine and TNF fusion protein was explained by F8-TNF causing rapid tumor hemorrhagic necrosis and as a result leaving small amount of residual cancer cells. In addition, was noticed a significant increase in AH1-specific CD8+ T cells in tumors and draining lymph nodes (60). IL-12 inhibited human colon cancer cells (HRT18, HT29, and HT115) motility and invasion, suggesting its important role in metastasis (41). IL-4 is actively released by colon cancer stem-like cells, and gives tumors a death-resistant phenotype. Neutralizing IL-4 with its antibody significantly sensitizes cancer cells to chemotherapy (49). Early transgenesis of IL-5 in colitis-assosiated CRC mouse model increased the severity of colitis, induced the rate of polyps formation and as a result higher tumor load (51). In patient was reported a case of extreme eosinophilia caused by IL-5 producing disseminated colon cancer (61). TGF-β promotes the survival, invasion and metastasis of CRC cells (53). TGB-β in the tumor microenvironment enhances T-cell exclusion and inhibits the excavation of Th-1 phenotype. Mice with metastatic colon cancer and blocked TGF-β signaling pathway have tumors sensitive to anti-PD-1 anti-PD-L1 therapy. In contrast, mice with unblocked TGF-β signaling, showed a limited response to immune checkpoint inhibitors (54). Systemic administration of IFN-α to mice with colon cancer significantly inhibited the growth of the tumor and its vascularization; induced apoptosis of tumor cells and in metastasis-associated hepatic endothelial cells (56).
Table 2. The main effects of pro- and anti-inflammatory cytokines.
Current Treatments of CRC
Finding the best choice of treatment can be done by combining and analyzing information about the tumor-associated factors (tumor localization, the presence of metastasis, the presence of biomarkers, etc.) and the patient-related factors (prognosis, concomitant diseases, etc.).
CRC patients with a metastatic disease receive a combination of chemotherapy and immunotherapy. The 1st line chemotherapy includes fluoropyrimidines such as capecitabine and 5-fluorouracil (5- FU) alone or with leucovorin (LV), oxaliplatin (5-FU/LV/oxaliplatin – FOLFOX), irinotecan (5-FU/LV/irinotecan – FOLFIRI), capecitabine/LV/oxaliplatin – CAPOX. The 2nd line chemotherapy – FOLFOX or CAPOX for patients who are resistant to irinotecan. Patients who are refractory for oxaliplatin combinations will be prescribed FOLFIRI or irinotecan as monotherapy. Usually, the treatment lasts up to 6 months, but the duration significantly depends on individual cases (62).
The most common side effects of chemotherapy for CRC are leukopenia, polyneuropathy, diarrhea, thrombocytopenia, hyperemesis, hepato-renal dysfunctions, and the deterioration of the general condition. The severity of side effects is usually more profound in elderly patients and in patients with preexisting comorbidities (63). Due to toxicity concerns, chemotherapy might not be suitable for many patients. Oncologists might not recommend this type of treatment due to some advanced stages of chronic diseases (liver, kidney, and heart failures) and a poor physical performance (64).
Immunotherapy is one of the most promising therapeutic modalities for patients with CRC (65). Targeted therapy has revolutionized cancer treatment. Immunotherapy is a type of curative approach that helps the immune system to eradicate tumors. It can be classified into two main groups: active (vaccines) and passive (monoclonal antibodies, adoptive cell therapy) (Table 3). Also, some biological therapies can particularly target certain designated tumor antigens, while others work non-specifically by enhancing the natural immune responses (75).
Table 3. Advantages and disadvantages of immunotherapeutic agents.
There are some types of cancer vaccines that have been studied in CRC treatment, such as a whole tumor -, peptide -, viral vector -, and dendritic cell (DC) vaccines. The aim of these agents like any other immunization strategy is to induce the antitumor immune response that will eradicate cancer and supply the organism with continuing surveillance to protect from its return.
Whole Tumor Vaccines
Some advantages of working with whole tumor vaccines are: they are easy to produce and are composed of all known and unknown tumor antigens. In contrast, the most significant disadvantage of these vaccines is a very low immunogenicity that can target normal cells and as a result, a low efficacy. Several approaches were made to augment the immunogenicity of whole tumor vaccines. A trial with Newcastle disease virus infection was performed that showed a 98% 2-year survival rate in resected CRC patients in comparison with 67% in patients who received a whole tumor vaccine combined with a Bacillus Calmette–Guérin (BCG) vaccine. The results suggest that the immunogenicity of these compounds has been improved (27).
Peptide vaccines are more specific for atumor-associated antigen, but the efficacy is still considerably low due to a small amount of T cell responses. A phase I/II trial performed in CRC patients showed that a combination of p53 vaccine with interferon-alpha elevated the amount of interferon-gamma (76). The next type of vaccine is called viral vector vaccines. They are specific for a tumor-associated antigen and naturally immunogenic. The drawback of using them is their ability to cause a cytokine storm. The most used viruses in CRC are adenoviruses, poxviruses, and alphaviruses. Most of these vaccines target a carcinoembryonic antigen (CEA), a protein expressed by CRCs. Preclinical data show that the recombinant Vaccinia virus expressing CEA (rV-CEA) can enhance the adaptive and innate immune responses in mice. Also, it suppressed the proliferation of colon adenocarcinoma in animal models. However, clinical trials done in patients with advanced stages of colorectal cancer demonstrated a lack of responses (77). The dendritic cell vaccines are characterized by the tumor-associated antigen specificity and generation of an organism’s own immune response. The negative aspects are high costs and a very time-consuming preparation process. After the complete excision of CRC liver metastasis, the phase II vaccine clinical trial showed fewer and delayed relapses in the vaccine arm in comparison with the observation arm (78). Results of DCs vaccines are very encouraging, and soon their efficacy can be significantly improved.
Adoptive Cell Transfer Therapy
Adoptive cell transfer therapy is another type of immunotherapy. The main advantages of this cure type are the elimination of the need to produce the immune response and high tumor specificity. In contrast, some disadvantages are high costs, long preparation time, and target-dependent toxicities. In this therapy, the autologous T cells are withdrawn from the tumor, lymph nodes or peripheral blood of a patient and modified ex vivo by making them expand and adding some co-stimulatory molecules and cytokines. Then a passive transfer of these T cells into the host is done for the direct tumor destruction. The most recent discovery of this type of passive immunotherapy is the development of engineered T cells that express the chimeric antigen receptors specifically for carcinoembryonic antigen (79). A phase I trial performed in patients with CRC resistant to the standard treatment protocol regimen by using the autologous T cells modified to express a murine CEA T cell receptor showed a significant decrease in serum CEA in all three patients; in one of them a clinical response by the presence of metastasis regression in the liver and lungs was demonstrated. At the same time, these patients experienced transient inflammatory colitis (80). The recently reported results of a case study in patients with advanced colorectal cancer showed a notable clinical response to the combination of capecitabine and adoptive cell transfer (αβT cells and NK cells) prescribed after laparoscopic resection of colon cancer and some liver metastasis. Two weeks after laparoscopy, a drastic increase in CEA levels was observed. Adoptive cell transfer allowed to decrease the serum level of CEA, eventually bringing it to normal. A noticeable size reduction of the unresectable liver metastasis was observed. During the follow-up examination in 19 months, no progression or relapse was noted, and the levels of CEA remained within normal limits (81).
Highly specific monoclonal antibodies have been very effective in cancer treatment for decades. Proteins against epidermal growth factor receptor (EGFR) and vascular endothelial growth factor (VEGF) in combination with chemotherapy have shown better outcomes of malignant CRC (mCRC). Anti-EGFR agents like Cetuximab or Panitumumab as a monotherapy or combined with cytotoxic drugs are prescribed only when there is an absence of KRAS mutations (62). Bevacizumab, a humanized monoclonal antibody against VEGF, suppress the tumor growth and angiogenesis as well as modulates the immune system of a host by increasing the population of B and T cells (82).
The dramatic efficacy of antibody-based immunotherapy was proven with the use of another type of monoclonal antibodies (mAbs) known as checkpoint inhibitors (ICIs). The currently used ICIs have been shown to provide significant clinical responses to patients with mCRC, specifically with the mismatch repair-deficient/microsatellite instability-high (dMMR-MSI-H) type. They target the inhibitory immune receptors: programmed cell death 1 (PD-1) and its ligand PD-L1, cytotoxic T-lymphocyte associated antigen 4 (CTLA-4). The latter one is expressed in the naive T-cells, effector T-cells, and regulatory T-cells (T-regs). It stimulates the deactivation of T-regs via binding to the antigen-presenting cells. The PD-1 receptor is present in the CD4, CD8 lymphocytes, NK cells, MDSCs, T-regs, and B cells. Together with its ligand, this receptor causes the exhaustion of T-cells by minimizing the tumor-infiltrating lymphocytes and T-cell proliferation. Consequently, tumors acquire immunoresistance. Anti-CTLA-4 and anti-PD-1 agents activate T cells and cause a stronger anticancer response (83). dMMR-MSI-H CRC tumors have a 20 times higher mutational load than mismatch repair proficient microsatellite instability low tumors (pMMR-MSI-L). Besides, they are more infiltrated by TILs, macrophages and have the elevated levels of immune-stimulatory cytokines compared with pMMR-MSI-L. The latter one has a less effective response to ICIs and a worse prognosis (84).
As of August 2020, there were three FDA-approved ICIs that were used for patients with dMMR-MSI-H mCRC. The first one was Nivolumab, an anti-PD-1 agent approved by the FDA in July 2017 after successful results of a phase II CheckMate 142 trial for the second-line treatment of patients with dMMR-MSI-H mCRC that progressed on treatment with oxaliplatin, fluoropyrimidine, and irinotecan. In this trial, it was reported that at 12 months of follow-up, the objective response rate was present in 31% of patients and 69% of control individuals. The 12-months progression-free survival (PFS) was 50%, and the overall survival (OS) was 73%. The most common side effects related to the therapy were pruritus, rash, diarrhea and fatigue. BRAF, KRAS mutations and PD-L1 expression did not affect the response to the prescribed targeted therapy (85).
The second ICI that FDA approved in May 2017 was Pembrolizumab, an anti-PD-1 substance, the efficacy of which was proven in phase one of the Keynote 016 trial. Initially, it was demonstrated that patients with mCRC dMMR-MSI-H experienced a 40% response rate (RR), while patients with pMMR-MSI-L – 0% RR. Later on, it was documented that a 2-year PFS was 53% in the first group. Severe side effects were present only in 14% of patients, including thrombocytopenia, leukopenia and pancreatitis. This curative monotherapeutic option was prescribed for dMMR-MSI-H mCRC patients who deteriorated on or after oxaliplatin, fluoropyrimidine, and irinotecan therapies.
The next immunotherapeutic approach approved by FDA for refractory CRC that progressed on oxaliplatin, fluoropyrimidine, irinotecan therapies was a combination of Nivolumab with Ipilimumab (anti-CTLA-4 agent). The approval was granted in July 2018, after the report of the results of the phase II CheckMate trial 142. During the follow-up at 13.4 months, the objective response rate was 54.7%, with a partial response−51.3%, a complete response−3.4%, and the disease control rate for 3 months or more−80%. PFS at 12 months was 71%, OS−85%. Thirteen percent of patients were obliged to stop treatment because of the drug-related side effects. This combination demonstrated the superior efficacy than anti-PD-1 monotherapy. But the adverse effects of grade 3–4 were more prominent in combination therapy compared with one agent treatment, 32–20%, respectively (86).
Concerning patients with pMMR-MSI-L, more research on immunotherapeutic regimens should be done. There is a need to find drugs that will target an immune response and will also promote the T-cell infiltration. Due to a low mutational and neoantigen load, it is difficult to reach these aims. Current regimens include radiotherapy, chemotherapy, and anti-angiogenic substances for enhancing the immune activation, the killing of tumor cells, and the elevation of tumor antigens. Later on, the treatment may be combined with ICIs and other biologics. There are currently some ongoing clinical trials that evaluate the effects of chemotherapy with either anti-PD-1, anti-PD-L1 ans external beam radiation therapies or radiofrequency ablation (87). The ongoing trial NCT01633970 phase Ib assessed the efficacy of Atezolizumab (anti-PD-L1) and Bevacizumab plus FOLFOX; it showed OS of 7% and stable disease in 64% of patients. Another approach that has been well-studied is a combination of the mitogen-activated protein kinase inhibitors (MEK) like Cobimetinib and Atezolizumab. MEK inhibitors can further sensitize MSS mCRC for targeted therapy. A phase Ib clinical trial (NCT01988896) assessed this combination in patients with refractory KRAS-mutant CRC and pMMR-MSI-L CRC and demonstrated RR of 17%, where five patients out of 23 had stable disease, and four patients developed PR. No advanced therapy-related adverse effects were noted. Later on, 84 patients were included, and results were updated. The RR was 8%, the disease control rate-−31%. The 6-month PFS and 12-month OS were 27 and 51%, respectively. This approach is very promising as it shows that MEK inhibitors can increase the response to immunotherapy in MSS mCRC patients. Some promising results were presented during the ongoing NCT03406871 trial that combined Nivolumab and Regofarenib (multi-kinase inhibitor); 18 out of 19 patients had objective tumor response (seven of which were MSS CRC, 11—MSS gastric cancer and 1—MSI-H CRC). More personalized approaches to treatment of pMMR-MSI-L are still required (84).
The Relevance of ECS To CRC
ECS actively regulates gut homeostasis. All components of ECS are highly expressed in the intestinal tissue, meaning that this system directly affect the proper functioning of gastro-intestinal system. CB1 and CB2 receptors are expressed in healthy colon epithelium, submucosal myenteric plexus, and smooth muscles, plasma cells in the lamina propria; CB2 receptor is also present on the intestinal macrophages (88, 89). TRPV1 receptor is expressed on colonic nerve fibers (90). The GPR55 receptor is present in the mucosa and the muscle layer of the colon (91). The endocannabinoids, 2-AG an AEA are also present in healthy colonic tissue (92). The main degradation enzymes of endocannabinoids, FAAH and MAGL enzymes are distributed on colonic epithelium glands, lamina propria, and myenteric plexus. The NAPE-PLD and DAGL biosynthetic enzymes are expressed on colonic smooth muscles, lamina propria, and epithelium glands; DAGL is also present on myenteric plexus (89).
To understand the role of ECS in the gut, it is important to distinguish the effects of increased and decreased cannabinoid tone in the gastro-intestinal system. In general, CB1 receptor antagonists reduce the cannabinoid tone in the gut and lead to vomiting, diarrhea, increased gastric emptying, and gastro-intestinal transit. In contrast, CB1 and CB2 receptor agonists, as well as MAGL inhibitors and FAAH blockers lead to an increase in intestinal cannabinoid tone by reducing vomiting, gastric acid secretion, and gastric emptying, as well as reducing hypermotility, diarrhea, and visceral pain (93). CB1 receptor silencing by selective CB1 receptor antagonist AM251 in ApcMin/+ mice led to an increase in the number of intestinal polyps, while CB1 receptor activation caused tumor cell death. In contrast, silencing of the CB2 receptor did not show any effect on polyp growth (94).
The components of ECS are significantly dysregulated in CRC. The endocannabinoids (2-AG and AEA) were 3-fold higher in adenomas and 2-fold higher in CRC in comparison to normal colon mucosa (92). The expression of CB1 receptor is decreased in CRC (95). The CB2 receptor expression is increased in CRC and is considered as a poor prognostic factor for this type of cancer (96). Levels of FAAH and MAGL were also increased in patients with CRC (97). ECS is a very important factor of CRC pathogenesis, suggesting a potential impact of cannabinoids in this disease.
The medicinal plant that has recently gained a lot of attention in the cancer field is Cannabis sativa. Many in vitro and in vivo experiments have shown that cannabinoids and cannabis extracts inhibit proliferation, stimulate apoptosis and autophagy, suppress angiogenesis and metastasis (98–100). The main active cannabinoids responsible for these effects are cannabigerol (CBG), cannabidiol (CBD), and tetrahydrocannabinol (THC). It was demonstrated that CBG activated apoptosis, prompted ROS production, increased CHOP mRNA, and suppressed cell growth in CRC cells (Caco-2, HCT-116) (101). It was found that the inhibitory effect of CBG on colorectal cancer cells viability was time dependent. In TRPM8 silenced cells, the inhibitory effect of CBG on cell growth was prominently suppressed in comparison with non-silenced cells. The induction of apoptosis was shown by an increase in the activity of caspases 3 and 7, the presence of DNA fragments, an increase in the expression of CHOP. In the same paper, it was shown that CBG (3 or 10 mg/kg) inhibited the growth of xenograft tumors (HCT-116) in a mouse model by 45.3% and chemically induced colon carcinogenesis in models by azoxymethane (AOM) in which CBG at a concentration of 5 mg/kg completely suppressed the formation of aberrant crypt foci (ACF), reduced the number of tumors by one half, and did not affect polyp formation (101).
CBD was also demonstrated to have the antiproliferative effects in colorectal cancer models. In some in vitro studies, CBD protected DNA from oxidative stress, elevated the levels of endocannabinoids, and suppressed colorectal cancer cell proliferation via CB1, TRPV1, PPAR-γ receptors (102). Selective antagonists rimonabant and AM251 (CB1R antagonist), capsazepine (TRPV1R antagonist), GW 9662 (PPAR-γ receptor antagonist) suppressed the antiproliferative effects of CBD. The chemoprevention of CBD was confirmed using in vivo models of AOM-induced colon cancer. CBD (1 mg/kg) reduced ACF by 67%, the number of tumors by 66% and polyps by 57%. When the concentration was elevated to 5 mg/kg, it only prevented the formation of polyps. This effect was due to the activation of caspase-3 and a decrease in the phosphorylated form of Akt-protein (102). In another study, the pro-apoptotic effect of CBD in CRC cells (HCT-116, DLD-1) was shown and was suggested to be the result of Noxa activation, the elevation of ROS production and the induction of endoplasmic reticulum stress. When the levels of Noxa were suppressed by siRNA, the expression of apoptosis markers became significantly reduced. Similarly, after the blockage of ROS production, the level of Noxa were reduced. CBD induced apoptosis in a Noxa-ROS-dependent manner (103). Moreover, while using CT26 cell line-induced colon cancer in mice, CBD at concentrations of 1 and 5 mg/kg was reported to have the anti-angiogenic and antimetastatic effects via the inhibition of VEGF, with the latter dose being more effective. In animals receiving CBD, a significant increase in the activity of antioxidant enzymes, including SOD, GPX, GR, TAC, and a decrease in MDA were noted (104).
The effects of full botanical extracts, such as high CBD botanical drug substance (BDS), on colon cancer were also studied. Such extracts are typically prepared from cannabis flowers that are rich in CBD, or CBD isolate is added (spiked) to a certain concentration. It was hypothesized that other components of cannabis plant extracts may act synergistically with CBD and can be useful from a therapeutic point of view. It was shown that CBD BDS had the significant antiproliferative properties on cancer cells (HCT-116, DLD-1), while healthy colonic epithelial cells were not affected. No difference was noted in the potency and efficacy between CBD BDS and CBD when the same doses were used (0.3–5 μM). CBD BDS effects were counteracted by selective antagonists to CB1 and CB2 receptors. CBD BDS had a more pronounced affinity to both CB1 and CB2 receptors than pure CBD. In vivo studies showed that using chemically induced carcinogenesis by AOM, C. sativa extract with a high content of cannabidiol inhibited ACF by 86%, polyps by 79% and tumor formation by 40%. In xenograft models, CBD BDS significantly reduced the tumor volume, but no difference in the growth of tumors was observed after 1 week of treatment (105).
THC was shown to induce apoptosis in colorectal cancer cells via the activation of CB1 receptors and the inhibition of PI3K-AKT, the RAS-MAPK cascade and BAD activation. Colorectal cancer cells (SW480, HCT-15, HT29, Caco-2, HCT-116, and SW620) that were exposed to THC (2.5–12.5 μM) resulted in a dose-dependent reduction in cell survival. In contrast, smaller concentrations from 100 nM to 1 μM had no noticeable effect on colorectal cancer cell proliferation and survival. THC increased the levels of caspase-3 and PARP (caspase-3 substrate). THC caused the dephosphorylation and activation of BAD (106). The anti-cancer potential of cannabinoids in CRC is summarized in Table 4.
Table 4. Cannabinoids anti-cancer potential in CRC.
Slow development and approval of new anti-neoplastic drugs for CRC is due to the lack of proper preclinical models. 2D in vitro models allow to perform high throughput screenings and are simple to work with, but allow only to study cell-to-cell or cell-to-matrix interactions, not a whole TME; that is why they are not physiologically relevant and not clinically predictive. On the other hand, in vivo animal models allow to study the whole organism interactions with proper TME and intra-tumor heterogeneity, but these models are not suitable for large scale screenings, are very time-consuming, and are not “human.” Thus, both, in vitro and in vivo models serve as a valuable tool to study colorectal carcinogenesis (107). However, due to mentioned differences, correlation between these models is not very strong (108). Clinical trials, on the other hand, are golden standard for testing and approval of any potential drug.
It is important to mention one clinical study that has investigated the largest number of cancer patients receiving medical cannabis between 2015 and 2017 in Israel. Two thousand nine hundred seventy patients suffering from the breast (20.7%), lung (13.6%), pancreatic (8.1%), and colorectal cancer (7.9%) were receiving medical cannabis as a palliative treatment to alleviate symptoms such as pain, poor appetite, malaise, sleep disorders, and nausea. Four types of cannabis were used in this study: sativa strains high in THC, without CBD; indica strains high in THC without CBD; strain with an equal amount of CBD and THC, and CBD-rich strains. Interestingly, most patients received more than one strain. Nine hundred two (24.9%) patients died and 682 (18.8%) patients terminated the treatment after 6 months of follow up. Out of the remaining patients, 60.6% of them responded to the treatment; 95.9% had a significant improvement in their condition, 3.7%—no change noticed, 0.3% -deteriorated. Before initiating the treatment, only 18.7% of patients said to have a good quality of life, while at 6 months post-treatment −69.5%. Among the all cancer-associated symptoms, nausea, vomiting, depression, migraine, and sleep disorders, were the most improved. The most common side effects of cannabis treatment at 6 months of follow up were dizziness, xerostomia, and increased appetite. The psychoactive adverse effects were noticed by 2.8% of patients only. Notably, out of 344 patients taking opioids, 36% of them discontinued taking them. It was concluded, that medical cannabis is a well-tolerated and safe palliative therapeutic option for cancer patients (109).
The Role of Cannabis on the Innate and Adaptive Immune Responses
Being immunomodulatory agents, cannabis extracts and single cannabinoids can affect both the innate and adaptive immune responses. Generally, cannabinoids are considered as immunosuppressive compounds. They influence the innate immune responses by suppressing the activity of NK cells, dendritic cells, the migration of neutrophils and macrophages with their antigen presentation and phagocytosis processes (110), and by triggering the induction of MDSCs (111, 112). Inflammation is the main mechanism of the innate immune responses. In general, cannabinoids, such as THC and CBD, cause the downregulation of pro-inflammatory cytokines and the upregulation of anti-inflammatory cytokines. By doing this, they actively suppress the inflammation process (57). However, some studies demonstrate that these compounds have different effects on inflammation by either enhancing or suppressing it. For example, CBD can activate the immune response by elevating mRNA expression of TNF-α, IL-6, as it was shown in mice in response to the LPS-induced pulmonary inflammation (113). In contrast, CBD inhibited IL-6 and IL-8 in an in vivo mouse colon cancer model based on the cell line CT26 (104). These contradicting results might be tissue- and dose-specific.
Cannabinoids may affect the adaptive immune responses by influencing the humoral and cellular immunity. The T cell immunity can be influenced by cannabinoids in different ways: they can affect the proliferation and the number of T cells by polarizing the cytokine response to either Th1 or Th2 (114). Cannabinoids have been shown to suppress the proliferation of T cells, to cause their apoptosis and support the Th2 polarization (115, 116). Some of the initial in vitro and in vivo studies of THC showed an immunosuppressive effect on the T cells and B cells when high concentrations were used, while the immunostimulatory effects was observed at low concentrations (110). The experimental research conducted in vivo with SIV-infected macaques that were receiving THC for the period of 17 months demonstrated an increase in T cells, the reduction in viral load and an increase in the expression of Th2 cytokines (117). Another study performed with HIV patients showed a higher concentration of CD4+ and CD8+ T cells in THC- positive patients vs. THC-negative counterparts (118). Concerning the role of CBD, it was also shown that it could act as an immunosuppressant of Th2 in vitro and in vivo by polarizing the cytokine response to Th2 and working as an immunostimulant to Th1 (119). Concerning the humoral immunity, some reports from human studies showed the reduced number of B lymphocytes and the decreased amount of IgM and IgG after cannabinoid ingestion in the form of bhang (120).
Future Perspectives of Enhancing Immunotherapy by Cannabinoids and Cannabis Sativa Extracts
The immunomodulatory effects of cannabis are well-documented. Nowadays, there are many well-known cannabis cultivars, and each one has a unique composition of different compounds. Many studies have demonstrated the effects of single cannabinoids, such as THC and CBD, on inflammation and cancer cell growth (98). Other components of the plant (such as minor cannabinoids, terpenes, terpenoids, flavonoids, and others) may act synergistically with cannabinoids and can be useful from a therapeutic point of view. The modulating effect of these compounds is known as “an entourage effect;” such modulation is typically positive which means that the medicinal effect of the whole plant extract is more significant than the effect of isolated compounds (121). Like with any other drug, the effects significantly depend on the concentration. In the future, with more research being done, we might gain more insight into the potential immunostimulatory effect of individual cannabinoids or cannabis extracts. This knowledge can help medical professionals to integrate cannabis extracts into cancer targeted therapy, potentially as adjunct therapy. The special extracts with strong anti-neoplastic activities should be identified that are not cytotoxic to normal cells and can sensitize cancer cells to further treatment without reducing the immune responses. Then, these extracts can be combined with immunotherapy, and such combination may have a synergistic action. The results of the retrospective analysis performed with patients with melanoma, renal carcinoma and non-small cell lung cancer when cannabis was used in combination with an immunotherapeutic agent Nivolumab showed a decrease in RR but no changes in PFS and OS. More studies are needed to investigate the possible interactions between cannabinoids and immunotherapy drugs (122).
A thorough exploration of cannabis research and associated drugs should be performed. Currently, we have limited data about cannabis interactions with other drugs, especially with targeted therapy. Since the immune checkpoint inhibitors are a type of the most successful and effective immunotherapy for CRC patients. Therefore, research on the possibility of enhancing the immunotherapy by cannabis extracts should be conducted (Figures 2, 3).
Figure 2. The potential of cannabinoids for cancer immunotherapy. The upper panel shows how cannabinoids can increase tumor immunogenicity. The release of tumor antigens might be increased due to the direct cytotoxicity of cannabinoids in cancer cells. Next, the presentation of enhanced tumor antigens occurs followed by an increase in T cells-mediated immune response and T cells lysis of tumor cells. The lower panel shows how cannabinoids can reverse tumor immunosuppression. Macrophages can be reprogrammed into an antitumor phenotype with the help of cannabinoids. M1 immunostimulatory macrophages secrete the anti-tumorigenic cytokines and effectively phagocytize cancer cells.