Management of Immune-Related Adverse Events in Patients Treated With Immune Checkpoint Inhibitor Therapy: American Society of Clinical Oncology Clinical Practice Guideline

Purpose To increase awareness, outline strategies, and offer guidance on the recommended management of immune-related adverse events in patients treated with immune checkpoint inhibitor (ICPi) therapy. Methods A multidisciplinary, multi-organizational panel of experts in medical oncology, dermatology, gastroenterology, rheumatology, pulmonology, endocrinology, urology, neurology, hematology, emergency medicine, nursing, trialist, and advocacy was convened to develop the clinical practice guideline. Guideline development involved a systematic review of the literature and an informal consensus process. The systematic review focused on guidelines, systematic reviews and meta-analyses, randomized controlled trials, and case series published from 2000 through 2017. Results The systematic review identified 204 eligible publications. Much of the evidence consisted of systematic reviews of observational data, consensus guidelines, case series, and case reports. Due to the paucity of high-quality evidence on management of immune-related adverse events, recommendations are based on expert consensus. Recommendations Recommendations for specific organ system-based toxicity diagnosis and management are presented. While management varies according to organ system affected, in general, ICPi therapy should be continued with close monitoring for grade 1 toxicities, with the exception of some neurologic, hematologic, and cardiac toxicities. ICPi therapy may be suspended for most grade 2 toxicities, with consideration of resuming when symptoms revert to grade 1 or less. Corticosteroids may be administered. Grade 3 toxicities generally warrant suspension of ICPis and the initiation of high-dose corticosteroids (prednisone 1 to 2 mg/kg/d or methylprednisolone 1 to 2 mg/kg/d). Corticosteroids should be tapered over the course of at least 4 to 6 weeks. Some refractory cases may require infliximab or other immunosuppressive therapy. In general, permanent discontinuation of ICPis is recommended with grade 4 toxicities, with the exception of endocrinopathies that have been controlled by hormone replacement. Additional information is available at www.asco.org/supportive-care-guidelines and www.asco.org/guidelineswiki .

Management of Immune-Related Adverse Events in Patients Treated With Immune Checkpoint Inhibitor Therapy: American Society of Clinical Oncology Clinical Practice Guideline

Purpose To increase awareness, outline strategies, and offer guidance on the recommended management of immune-related adverse events in patients treated with immune checkpoint inhibitor (ICPi) therapy. Methods A multidisciplinary, multi-organizational panel of experts in medical oncology, dermatology, gastroenterology, rheumatology, pulmonology, endocrinology, urology, neurology, hematology, emergency medicine, nursing, trialist, and advocacy was convened to develop the clinical practice guideline. Guideline development involved a systematic review of the literature and an informal consensus process. The systematic review focused on guidelines, systematic reviews and meta-analyses, randomized controlled trials, and case series published from 2000 through 2017. Results The systematic review identified 204 eligible publications. Much of the evidence consisted of systematic reviews of observational data, consensus guidelines, case series, and case reports. Due to the paucity of high-quality evidence on management of immune-related adverse events, recommendations are based on expert consensus. Recommendations Recommendations for specific organ system-based toxicity diagnosis and management are presented. While management varies according to organ system affected, in general, ICPi therapy should be continued with close monitoring for grade 1 toxicities, with the exception of some neurologic, hematologic, and cardiac toxicities. ICPi therapy may be suspended for most grade 2 toxicities, with consideration of resuming when symptoms revert to grade 1 or less. Corticosteroids may be administered. Grade 3 toxicities generally warrant suspension of ICPis and the initiation of high-dose corticosteroids (prednisone 1 to 2 mg/kg/d or methylprednisolone 1 to 2 mg/kg/d). Corticosteroids should be tapered over the course of at least 4 to 6 weeks. Some refractory cases may require infliximab or other immunosuppressive therapy. In general, permanent discontinuation of ICPis is recommended with grade 4 toxicities, with the exception of endocrinopathies that have been controlled by hormone replacement. Additional information is available at www.asco.org/supportive-care-guidelines and www.asco.org/guidelineswiki .

An update on the Society for Immunotherapy of Cancer consensus statement on tumor immunotherapy for the treatment of cutaneous melanoma: version 2.0

BACKGROUND

Cancer immunotherapy has been firmly established as a standard of care for patients with advanced and metastatic melanoma. Therapeutic outcomes in clinical trials have resulted in the approval of 11 new drugs and/or combination regimens for patients with melanoma. However, prospective data to support evidence-based clinical decisions with respect to the optimal schedule and sequencing of immunotherapy and targeted agents, how best to manage emerging toxicities and when to stop treatment are not yet available.

METHODS

To address this knowledge gap, the Society for Immunotherapy of Cancer (SITC) Melanoma Task Force developed a process for consensus recommendations for physicians treating patients with melanoma integrating evidence-based data, where available, with best expert consensus opinion. The initial consensus statement was published in 2013, and version 2.0 of this report is an update based on a recent meeting of the Task Force and extensive subsequent discussions on new agents, contemporary peer-reviewed literature and emerging clinical data. The Academy of Medicine (formerly Institute of Medicine) clinical practice guidelines were used as a basis for consensus development with an updated literature search for important studies published between 1992 and 2017 and supplemented, as appropriate, by recommendations from Task Force participants.

RESULTS

The Task Force considered patients with stage II-IV melanoma and here provide consensus recommendations for how they would incorporate the many immunotherapy options into clinical pathways for patients with cutaneous melanoma.

CONCLUSION

These clinical guidleines provide physicians and healthcare providers with consensus recommendations for managing melanoma patients electing treatment with tumor immunotherapy.

Predicting response to checkpoint inhibitors in melanoma beyond PD-L1 and mutational burden

BACKGROUND

Immune checkpoint inhibitors (ICIs) have changed the clinical management of melanoma. However, not all patients respond, and current biomarkers including PD-L1 and mutational burden show incomplete predictive performance. The clinical validity and utility of complex biomarkers have not been studied in melanoma.

METHODS

Cutaneous metastatic melanoma patients at eight institutions were evaluated for PD-L1 expression, CD8+ T-cell infiltration pattern, mutational burden, and 394 immune transcript expression. PD-L1 IHC and mutational burden were assessed for association with overall survival (OS) in 94 patients treated prior to ICI approval by the FDA (historical-controls), and in 137 patients treated with ICIs. Unsupervised analysis revealed distinct immune-clusters with separate response rates. This comprehensive immune profiling data were then integrated to generate a continuous Response Score (RS) based upon response criteria (RECIST v.1.1). RS was developed using a single institution training cohort (n = 48) and subsequently tested in a separate eight institution validation cohort (n = 29) to mimic a real-world clinical scenario.

RESULTS

PD-L1 positivity ≥1% correlated with response and OS in ICI-treated patients, but demonstrated limited predictive performance. High mutational burden was associated with response in ICI-treated patients, but not with OS. Comprehensive immune profiling using RS demonstrated higher sensitivity (72.2%) compared to PD-L1 IHC (34.25%) and tumor mutational burden (32.5%), but with similar specificity.

CONCLUSIONS

In this study, the response score derived from comprehensive immune profiling in a limited melanoma cohort showed improved predictive performance as compared to PD-L1 IHC and tumor mutational burden.

Immunological correlates of response to immune checkpoint inhibitors (ICI) in metastatic urothelial carcinoma (mUC) patients (pts)

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Background: Identification of biomarkers predictive of response to ICI could help guide treatment (tx) decisions. We assessed the correlation between PD1/PDL1 expression in key immunomodulatory subsets (myeloid-derived suppressor cells [MDSC]; CD8+ T cells) and tx response in mUC pts treated with ICI. Methods: Serial peripheral blood samples were collected from mUC pts treated with ICI. Flow cytometry was used to quantify PD1/PDL1 expression in MDSC (CD33+HLADR−) and CD8+ T cells (CD8+CD4−) from live peripheral blood mononuclear cells. MDSC were subdivided into monocytic (M)-MDSC (CD14+CD15−), polymorphonuclear (PMN)-MDSC (CD14− CD15+), and immature (I)-MDSC (CD14− CD15−). Mixed-model regression and Wilcoxon rank-sum tests were performed to assess post-ICI changes in immune marker expression and identify correlations between PD1/PDL1 expression and best overall response (BOR) to ICI. Results: Of 36 ICI-treated pts with ≥2 blood samples, 24 received anti-PDL1 (22 atezolizumab/2 avelumab; [A]) and 12 received anti-PD1 (pembrolizumab [P]). 78% were men, median age 69 (46–81), 28% never smokers, 19% had prior intravesical BCG, 39% prior neoadjuvant chemotherapy, and 64% prior cystectomy. BOR to ICI included 3 PR/14 SD/7 PD (A) and 1 CR/2 PR/6 SD/3 PD (P). Successive doses of A correlated with decreased %PDL1+ M-MDSC (mean change −5.26/dose; p = 0.009), while those of P correlated with decreased %PD1+ M- and I- MDSC (mean change −1.55 and −1.14/dose; p = 0.04 and 0.02, respectively). Though pre-tx %PD1+ CD8+ T cells did not predict BOR, greater PD1 expression by CD8+ T cells within 12 weeks after ICI initiation correlated with BOR (Table). Conclusions: ICI tx correlated with distinct changes in PD1/PDL1 expression by specific peripheral immune cell subsets. Responders to ICI had higher % of PD1+ CD8+ T cells after ICI than non-responders, though pre-tx % were comparable between groups. Further validation of these and other potential blood/tissue biomarkers is ongoing. [Table: see text]

Targeting autophagy and immunotherapy with hydroxychloroquine and interleukin 2 in patients with metastatic renal cell carcinoma (mRCC): A Cytokine Working Group study

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Background: We performed a Phase II study of the combination of the autophagy inhibitor, hydroxychloroquine (HCQ), along with high dose IL-2 in patients with advanced renal cancer. 31 patients were entered on this Cytokine Working Group Study conducted at six member institutions;NCT01550367. This combination in murine models was associated with diminished toxicity and increased efficacy, and, in preliminary studies, diminished high mobility group box 1 (HMGB1) protein, consistent with its established role in serving as a Damage Associated Molecular Pattern (DAMP) molecule and inducer of autophagy. Methods: The Study Design involved initiating oral Hydroxychloroquine 300 mg P.O bid. Aldesleukin (600,000 IU/kg) was administered q8hrs in courses consisting of two cycles separated by 7-14 days and constituting a single course. For patients with stable or responsive disease, additional courses were administered every approximately 85-90 days. Serum, plasma, Paxgene tubes, and peripheral blood mononuclear cells were obtained sequentially prior to therapy initiation and sequentially on D1 and D2 of each cycle following initiation of therapy. Results: 31 patients (9F, 22M) have been registered and 3 confirmed complete responses observed; the current median overall survival has not been reached in the 29pts. The Baseline Karnofsky Score of 100 (17pts), 90 (13pts), and 80(1 pt). The mean age was 57.5 years, range = (45.2, 68.8). 26 patients had a mean of 12.5 doses +/-4.7 (3, 23) with 13 pts receiving a second course and 4, a third. Platelet nadir was diminished from baseline by 26%. Of the 27 patients in the data set, 18 had at least one Grade 4 toxicity at least possibly related to treatment, and 9 patients had at least one Grade 3 adverse event at least possibly related to treatment but no Grade 4 events.Serologic and cellular data and complete clinical data will be submitted with the completed abstract. Conclusions: The combination of high dose aldesleukin and daily oral HCQ was well tolerated. We have concluded this trial and will report mature survival data, toxicity data, and biomarkers/autophagy measures with the final submission. Clinical trial information: NCT01550367.

Neoadjuvant combination immunotherapy with pembrolizumab and high dose IFN-α2b in locally/regionally advanced melanoma

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Background: Neoadjuvant pembrolizumab at 200 mg in combination with high dose IFNα2b (HDI) for locally/regionally advanced or recurrent melanoma may improve the clinical outcomes of these high risk patients (pts), and provide access to blood and tumor pre/post pembro-HDI to illuminate the host effector and suppressor immune mechanisms. Methods: Pts were treated with pembro 200 mg IV every 3 weeks (wk) x 2 doses followed by definitive surgery, then every 3 wks for up to one year. HDI (20 MU/m²/d IV x 5 days (d)/wk for 4 wks then 10 MU/m²/d SC every other d TIW for 48 wks) was given concurrently. Tumor samples were obtained at baseline and at definitive surgery (wk 6-8) and serum/PBMC at baseline, 6 wks, 3, 6, 12 months (mo). Results: Twenty evaluable pts (14 male, 6 female, 14 cutaneous primary, 4 unknown, 3 mucosal), age 29-82 were treated. 5 had Stage IIIB (N1b, N2b, M2c), 11 IIIC (N3) and 4 IV (M1a, M1b) melanoma. Over 230 cycles have been delivered to date (median 14). Worst toxicities included grade (Gr) 3: fatigue (8; 40%), ↑CPK (5; 25%), hypophosphatemia (5; 25%), ↑lipase (3; 15%), lymphopenia (3; 15%), hypertension (2; 10%), diarrhea/colitis (1; 5%), arthralgia (1, 5%), syncope (1, 5%), hyponatremia (1, 5%), neutropenia (1; 5%), anemia (1, 5.00%) nausea (2, 10%), flu like symptoms (1, 5%). There were 3 Gr 4 events (CPK, hyperglycemia, lymphopenia). One suspected grade 5 event occurred 6 months after completion of therapy with autopsy evidence of pneumonia and myocarditis. Among 20 evaluable pts, 4 relapsed and 1 died. Median follow-up for pts who have not relapsed is 11 months. The radiologic preoperative response rate (WHO; unconfirmed) was 65%. The pathologic complete response rate (no viable tumor on histologic assessment) was 35%. Conclusions: Neoadjuvant pembro-HDI exhibited promising clinical activity. Longer follow up is underway in order to define the long term benefits and risks. Clinical trial information: NCT02339324.

Immune deserts: Correlation of low CD8 gene expression with non-response to checkpoint inhibition

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Background: Associations between presence and density of effector T-cells (CD8+) and response to checkpoint inhibitors (CPIs) has been established for protein biomarkers using immunohistochemistry but less work has been done to characterize this relationship through gene expression. Methods: We collected clinical response data (RECIST v1.1) for 184 patients who had been treated with CPIs across tumor types with FDA indications. We tested formalin-fixed paraffin embedded (FFPE) samples by NGS with a comprehensive immune response panel which interrogates the gene expression profile of 54 validated immune-related genes. Ranked gene expression was compared to a reference population. 85/184 (46%) cases were considered “responders” after six months, and 66/184 cases (36%) were considered responders after twelve months on treatment. We hypothesized that patients with in the bottom quartile of CD8 expression, as measured by the rank of the sum of normalized CD8A and CD8B transcripts compared to a reference population, would be unlikely to respond to checkpoint therapy (immune deserts), and that “hot” tumor environments (TME) with the highest quartile of expression would be most likely to respond. Results: After six months of therapy, 13/40 (32.5%) patients with immune desert tumors responded to therapy, whereas 39/82 patients (47.6%) in the middle 50% of expression responded, and 33/62 (53.2%) of patients with “hot” TME responded to treatment. The two-tailed p-value of the null hypothesis, that TME status does not correlate with response, was 0.018 and could be rejected. After twelve months of observation, 9/40 (22.5%) immune desert patients were considered “responders”. 28/82 (34.2%) of the middle 50% of expression were classified as responders, and 29/62 (46.8%) of top quartile samples came from responders. The two-tailed p-value of the null hypothesis was 0.005 and could be rejected. Conclusions: Gene expression of CD8 as measured by RNA-seq from FFPE samples can be used to compare these samples versus a reference population to predict an increase or decrease in likelihood of response to CPIs. Patients in the lowest quartile of CD8 expression were the least likely to respond to these promising therapies.

Effect of CTLA-4 overexpression on response to ipilimumab in melanoma

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Background: CD8 positive tumor infiltrating lymphocytes (TILS) are highly associated with immune response and prognosis, and are also under investigation as a marker of response to checkpoint inhibitors. Given lack of predictive biomarkers for ipilimumab, growing number of trials for new indications for combination ipilimumab + nivolumab, and evidence to support therapeutic target overexpression as markers of response, we examined the role of CTLA-4 expression and TILS in response to ipilimumab and combination ipilimumab + nivolumab in melanoma. Methods: Formalin-fixed paraffin embedded melanoma samples taken prior to treatment by ipilimumab (n = 36) or combination ipilimumab + nivolumab (n = 10) were evaluated by a comprehensive immune gene expression profile to establish the relationship between CTLA-4 and CD8 and therapeutic response (RECIST v1.1). Results: Increased CTLA-4 expression was moderately associated with increased TILS (r2= .41, p = .004). This was observed in the monotherapy group (r2= .38, p = .02), and was higher in the smaller combination therapy group, though not statistically significant (r2= .59, p = .06). Higher levels of TILS were observed in responders who achieved clinical benefit from either regimen within 6 months (n = 20). No significant difference was observed between responders (M = 57.1, SD = 30.2) and nonresponders (M = 48.6, SD = 32.9); t(44) = -.895, p = .376. Lower levels of CTLA-4 were observed in responders who achieved clinical benefit from either regimen within 6 months. No significant difference was observed between responders (M = 54, SD = 35) and nonresponders (M = 38.7, SD = 26.8); t(44) = 1.70, p = .09. The ratio of TILS to CTLA-4 expression was higher in responders who achieved clinical benefit within 6 months (n = 20).No significant difference was observed between responders (M = 5.2, SD = 14.0) and nonresponders (M = 1.4, SD = 2.7); t(41) = -1.2, p = .212. Conclusions: While not statistically significant, CTLA-4 expression in melanoma patients treated with either ipilimumab or combination ipilimumab + nivolumab was lower in responders compared to nonresponders. This analysis does not support the concept that over-expression of CTLA-4 is a biomarker of response to anti-CTLA-4 therapy.

Serial changes in PD1/PDL1 expression in metastatic urothelial carcinoma (mUC) patients (pts) treated with immune checkpoint blockade (CPB)

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Background: Since CPB may alter immune marker expression in key immunomodulatory populations such as myeloid-derived suppressor cells (MDSC) and CD8+ cytotoxic T lymphocytes (CTL), we evaluated PD1/PDL1 expression in longitudinal samples from mUC pts treated with CPB. Methods: Serial peripheral blood samples were collected from mUC pts who received CPB. PD1/PDL1 and VISTA expression was measured in MDSC (CD33+HLADR−) and CTL (CD8+CD4−) from live peripheral blood mononuclear cells using flow cytometry. MDSC subsets were further defined as (G)ranulocytic (CD15+CD14−), (M)onocytic (CD15−CD14+), and (I)mmature (CD15−CD14−). PD1/PDL1 and VISTA expression was presented as % of each MDSC subset or CTL. Wilcoxon signed-rank tests and mixed-model regression analyses were performed to assess changes in immune marker expression after CPB. Results: Of 30 CPB-treated pts with ≥ 2 blood samples for analysis, 21 received anti-PDL1 (20 atezolizumab/1 avelumab; [A]) and 9 received anti-PD1 (pembrolizumab [P]). Median age at diagnosis was 69.5 (46–81), 77% men, 33% never smokers, 63% pure UC, 70% bladder primary, 20% prior intravesical BCG, 37% prior neoadjuvant chemotherapy, 63% prior cystectomy. Best overall responses to CPB were 3 PR/13 SD/5 PD (A) and 1 CR/1 PR/4 SD/3 PD (P). Successive doses of A correlated with decreased %PDL1+ M-MDSC, while those of P correlated with decreased %PD1+ M- and I- MDSC (Table). No significant changes in VISTA expression were detected. In 11 A-treated pts with samples before/after the 1st dose, %PDL1+ M- and I- MDSC decreased (median change −25.5 and −5.7; p = 0.02 and 0.03) and %PD1+ CTL increased (median change +2.4; p = 0.02) between 1st and 2nd samples. Conclusions: In this mUC pt cohort, distinct post-tx changes in %PD1/PDL1 in MDSC subsets and CTL occurred based on CPB (anti-PD1 vs anti-PDL1). Further analysis of correlations between CPB, immune marker expression, clinicopathologic factors, and outcomes is ongoing in a larger cohort. Mean absolute change in marker expression per dose in pts treated with CPB. [Table: see text]

Correlation of lung cancer mutational profile with immune profile

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Background: The association between neoplasm mutational and immune profiles has not been well-characterized. Methods: We collected 26 lung cancer formalin-fixed paraffin embedded (FFPE) samples which had been tested with a comprehensive mutation profile to detect clinically actionable mutations, and a comprehensive immune gene expression profile, which interrogates PD-L1 immunohistochemistry (IHC), PD-L1/2 copy number, CD3/CD8 IHC, microsatellite instability status, mutational burden, and the expression profile of 54 immune-related genes. The ranking of gene expression and 7 immune phenotypes was compared to a reference population. Six cases were positive for an activating KRAS mutation and 2 cases were positive for an activating EGFR mutation. Principal component analysis was performed to determine the association of EGFR/KRAS mutations with the measured immune landscape. Results: The proinflammatory immune phenotype was significantly correlated with KRAS mutation positive samples (first principal component, R squared = 0.53, p < 0.05). Similarly, CD38 expression was correlated with KRAS mutation (R squared = 0.47, p < 0.05). CD137, KLRD1, and DDX58 expression was significantly correlated with EGFR positive samples (second principal component, R squared = 0.47, 0.37, 0.35 respectively, p < 0.05 in all cases). Unsupervised hierarchical clustering of the samples resulted in three distinct clusters, EGFR positive, KRAS positive, and EGFR negative/KRAS negative. In the KRAS positive cluster, high proinflammatory immune phenotype, VISTA moderate expression, presence of CD3/CD8 tumor infiltrating lymphocytes (TILs), and low KLRD1 were overrepresented (p < 0.05), while low VISTA and proinflammatory moderate immune phenotype were significantly underrepresented (p < 0.05). In the EGFR positive cluster DDX58 high, very low TILs, and very low CD8 were significantly (p < 0.05) overrepresented. Conclusions: KRAS mutation positivity is significantly associated with a proinflammatrory immune phenotype and CD3/CD8 infiltration. KRAS positive, EGFR positive, and KRAS/EGFR negative clusters are immunophenotypically distinct. A higher number of specimens is necessary to verify and expand these findings.

Comprehensive immune and mutational profile of melanoma

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Background: The association between tumor mutational profiles and immune signatures has not been well-characterized. Methods: 306 melanoma samples were tested by NGS using a comprehensive cancer panel for mutational status and an immune response panel which interrogates the expression profile of 54 validated immune-related genes. The ranking of gene expression, mutational burden and 7 immune phenotypes was compared to a reference population. 38% cases were positive for activating BRAF mutations, 12% for RAS, and 6% for NF1. The remaining 44% were considered triple wild type. Principal component analysis (PCA) followed by hierarchical clustering was performed to determine association of BRAF/RAS/NF1 mutations and triple wild type with immune phenotypes, mutational burden and gene expression as measured by the NGS panels. Results: PCA showed that the first and second dimension explain 86% of the variation in the mutation profiles of the 306 melanomas. The first principal component highly correlated with BRAF positive status (pval < 0.001), the second highly correlated with RAS positive status (pval < 0.001), and the third principal component, although not informative, highly correlated with NF1 status (pval < 0.001) and Mutation Burden (pval < 0.001). Hierarchical clustering of the samples resulted in 4 distinct clusters: RAS positive, BRAF Positive, NF1 positive and triple wild type. The RAS positive cluster demonstrated significantly lower expression of ICOSLG, ICOS, CD4, C10orf54, CD40 and CD244 genes. Similarly, the BRAF positive cluster under-expresses immune escape and proinflammatory immune phenotypes, but over-expressed OX40L. The NF1 positive cluster had significantly higher mutational burden than other clusters. On the contrary, the triple wild type cluster over-expressed 6 out of 7 immune phenotypes. Conclusions: BRAF/RAS/NF1 mutation status are immunophenotypically distinct and do not associate with a typical immune phenotype in the tumor microenvironment. Triple wild type samples present with an overall activated immune phenotype, representative of an inflamed tumor. Additional studies are necessary to include additional activating or loss of function mutations to expand these findings.

Managing toxicities associated with immune checkpoint inhibitors: consensus recommendations from the Society for Immunotherapy of Cancer (SITC) Toxicity Management Working Group

Cancer immunotherapy has transformed the treatment of cancer. However, increasing use of immune-based therapies, including the widely used class of agents known as immune checkpoint inhibitors, has exposed a discrete group of immune-related adverse events (irAEs). Many of these are driven by the same immunologic mechanisms responsible for the drugs' therapeutic effects, namely blockade of inhibitory mechanisms that suppress the immune system and protect body tissues from an unconstrained acute or chronic immune response. Skin, gut, endocrine, lung and musculoskeletal irAEs are relatively common, whereas cardiovascular, hematologic, renal, neurologic and ophthalmologic irAEs occur much less frequently. The majority of irAEs are mild to moderate in severity; however, serious and occasionally life-threatening irAEs are reported in the literature, and treatment-related deaths occur in up to 2% of patients, varying by ICI. Immunotherapy-related irAEs typically have a delayed onset and prolonged duration compared to adverse events from chemotherapy, and effective management depends on early recognition and prompt intervention with immune suppression and/or immunomodulatory strategies. There is an urgent need for multidisciplinary guidance reflecting broad-based perspectives on how to recognize, report and manage organ-specific toxicities until evidence-based data are available to inform clinical decision-making. The Society for Immunotherapy of Cancer (SITC) established a multidisciplinary Toxicity Management Working Group, which met for a full-day workshop to develop recommendations to standardize management of irAEs. Here we present their consensus recommendations on managing toxicities associated with immune checkpoint inhibitor therapy.

Challenges faced when identifying patients for combination immunotherapy

In 1996, Jim Allison demonstrated that blocking the immune regulatory molecule CTLA-4 with anit-CTLA4 antibody led to enhance tumor responses in mice. It would take an additional 15 years for human studies to confirm the potency and clinical efficacy of anti-CTLA4, ultimately leading to US FDA approval of the first checkpoint inhibitor, ipilimumab. Now with a plethora of immune-modulating agents demonstrating single agent safety and benefit across many tumor types, investigation on the optimal combination of immune-based therapies has begun in earnest. While there are many challenges, a central one is how to select which combination for which patient is the best. Here we review the current approaches that a practitioner can use to achieve this therapeutic goal.

Cell cycle perturbation induced by gemcitabine in human tumor cells in cell culture, xenografts and bladder cancer patients: implications for clinical trial designs combining gemcitabine with a Chk1 inhibitor

Gemcitabine irreversibly inhibits ribonucleotide reductase and induces S phase arrest but whether this occurs in tumors in mice or patients has not been established. Tumor cells in culture were incubated with gemcitabine for 6 h to approximate the administration schedule in a patient. Concentrations that induced persistent S phase arrest thereafter correlated with cell killing. Administration of gemcitabine to mice also demonstrated a persistent S phase arrest in their tumor. The minimum dose that induced almost complete S phase arrest after 24 h (40 mg/kg) was well below the maximum tolerated dose in mice. S phase arrest was also observed in tumors of bladder cancer patients receiving gemcitabine. The Chk1 inhibitor MK-8776 sensitized cells to gemcitabine with the greatest cell killing when added 18 h after gemcitabine. In mice, the administration of MK-8776 18 h after gemcitabine elicited positivity for the DNA damage marker γH2AX; this also occurred at relatively low dose (40 mg/kg) gemcitabine. Hence, in both cell culture and xenografts, MK-8776 can markedly enhance cell killing of cells reversibly arrested in S phase by gemcitabine. Some cell lines are hypersensitive to MK-8776 as monotherapy, but this was not observed in xenograft models. Effective monotherapy requires a higher dose of Chk1 inhibitor, and target inhibition over a longer time period as compared to its use in combination. These results have important implications for combining Chk1 inhibitors with gemcitabine and suggest that Chk1 inhibitors with increased bioavailability may have improved efficacy both in combination and as monotherapy.

Algorithmic prediction of response to checkpoint inhibitors: Hyperprogressors versus responders

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Background: Predicting response to checkpoint inhibitors (CPIs) using biological knowledge-based decision processes with machine learning (ML) has a great potential to predict rapid progression in patients treated with checkpoint inhibitors (CPIs) (hyperprogressive disease (HPD)) as well as responders. ML models risk overfitting data and do not always evaluate the underlying biology, thus performing well in the initial training cohort but lack generalizability when extended to other cohorts. Biology-based decision may not perform as well initially due to limited understanding and a simplified rule set, but often perform equally well when extended to larger similar cohorts of patients. Methods: A custom NGS cancer immune gene expression assay compared 87 patients treated with CPIs classified as CR, PR, or SD versus 12 HPD. A ML-based polynomial regression model based on 54 immune-related genes combined with mutational burden was optimized for prediction of response. A biological 4-gene decision tree model was constructed independently based on ML. A second biological decision tree incorporated the weighted average relative rank of the expression of multiple genes in 4 different immune functions including immune cell infiltration, regulation, activation, and cytokine signaling. Bayesian model average (BMA) incorporated all three models’ results into the final prediction. Results: For87 patients classified as CR, PR, or SD the PPV >96% for responders and a NPV >90% for non-responders was achieved with the regression model, however with response indeterminate for 24% of the population. While the two biological decision tree models’ PPV were in the 70% range, they accurately revealed the critical genes’ roles in immune response with strong literature support. BMA process integrated these three models resulted in a PPV >96% and a NPV >90% and eliminated the indeterminate group. For HPD a unique biology related to priming of short term memory T-cells was identified. Conclusion: Prediction of response to CPIs is best attained by combining ML with biological knowledge. Decision tree models using a large panel of immune related genes in the context of archival samples from patients treated with CPIs can be used to better understand the biology of responders versus non-responders and provides new insights into HPD.

Serial measurements of myeloid derived suppressor cells (MDSC) in metastatic urothelial carcinoma (mUC) patients (pts) treated with immune checkpoint inhibitors (CI)

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Background: MDSC are a heterogeneous population of immunosuppressive cells with potentially predictive implications in UC pts receiving CI. We hypothesized that MDSC populations may change after CI exposure. Methods: Serial peripheral blood samples were collected from mUC pts treated with CI. MDSC were measured in fresh unfractionated whole blood (WB) and in peripheral blood mononuclear cells (PBMC). MDSC were identified by flow cytometry in WB and defined as LinloCD33+/HLADR- [(T)otal MDSC]. MDSC subsets were defined as (G)ranulocytic (CD15+CD14-), (M)onocytic (CD15-CD14+), (I)mmature (CD15-CD14-), or CD11b+. MDSC populations were presented as % of live nucleated blood cells and as absolute numbers from WB. The Wilcoxon signed rank and rank sum tests were used to assess changes in MDSC populations while on CI. Results: 17 pts treated with CI (9 atezolizumab [A], 8 pembrolizumab [P]) had ≥ 2 MDSC samples for analysis. Median age at diagnosis was 71 (46-81), 12 men, 29% never smokers; 53% / 29% / 18% ECOG PS 0/1/2 and 59% visceral metastasis at the time of 1st sample collection. 10 pts received CI as 1st line therapy (Tx) in metastatic setting; 7 pts received chemotherapy as 1st-line Tx for mUC (6 platinum-based, 1 docetaxel) and CI as 2nd-line Tx. In 16 pts with samples before 1stdose, there was a relative decrease (median 36.3%, range -59.7 to +21.2) in PBMC % I-MDSCs between 1st and 2nd samples (p=0.06). Interestingly, PBMC %M-MDSC and %I-MDSC tended to increase compared to baseline in pts treated with P, while they tended to decrease in pts treated with A (Table). Conclusions: In this cohort of pts with mUC treated with CIs,MDSC changes differed based on CI (anti-PDL1 or anti-PD1). Further study in larger cohort with various prior Tx lines and longer follow up as well as correlations with Tx response, toxicity and outcomes are ongoing. [Table: see text]

Efficacy and safety of nivolumab (NIVO) plus ipilimumab (IPI) in patients with melanoma (MEL) metastatic to the brain: Results of the phase II study CheckMate 204

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Background: Brain metastases (BMts) are a major cause of morbidity/death in MEL. We report the first efficacy data in MEL patients (pts) with BMts who received NIVO+IPI in study CheckMate 204. Methods: In this multicenter US trial (NCT02320058), MEL pts with ≥1 measurable BMt 0.5-3.0 cm and no neurologic symptoms or steroid Rx received NIVO 1 mg/kg + IPI 3 mg/kg Q3W x 4, then NIVO 3 mg/kg Q2W until progression or toxicity. Pts with severe adverse events (AEs) during NIVO+IPI could receive NIVO when toxicity resolved; stereotactic radiotherapy (SRT) was allowed for brain oligo-progression if an assessable BMt remained. The primary endpoint was intracranial (IC) clinical benefit rate (complete response [CR] + partial response [PR] + stable disease [SD] > 6 months). The planned 90-pt accrual is complete; we report efficacy and updated safety for 75 pts with disease assessment before the Nov 2016 database lock. Results: Median age was 59 yrs (range 22–79). Median number of induction doses was 3; 26 pts (35%) received 4 NIVO+IPI doses and 38 pts (51%) began NIVO maintenance. Response data are reported at a median follow-up of 6.3 months (Table). The IC objective response rate (ORR) was 56% (95% CI: 44–68); 19% of pts had a complete response. IC and extracranial responses were largely concordant. Rx-related grade 3/4 AEs occurred in 48% of pts, 8% neurologic, including headache and syncope. Only 3 pts (4%) stopped Rx for Rx-related neurologic AEs. One pt died of immune-related myocarditis. Conclusions: In CheckMate 204, prospectively designed to investigate NIVO+IPI in MEL pts with BMts, NIVO+IPI had high IC antitumor activity with objective responses in 56% of pts, CR in 19%, and no unexpected neurologic safety signals. The favorable safety and high anti-melanoma activity of NIVO+IPI may represent a new Rx paradigm for pts with asymptomatic MEL BMts and could change practice to avoid or delay whole brain RT or SRT. Clinical trial information: NCT02320058. [Table: see text]