Citations

Abstract Background: Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of patients with deficient DNA mismatch repair (d-MMR) cancers, yet less than half of patients with metastatic colorectal cancer (mCRC) receive clinical benefit. We analyzed heterogeneity within d-MMR tumors using a multi-omics approach inclusive of percent unstable microsatellite loci (MS). Methods: We studied consecutive patients with d-MMR mCRC with available primary tumors (N=32) that were treated with an anti-PD-1 antibody at Mayo Clinic (2015-2022). Tumors were profiled using a whole exome and transcriptome platform (ImmunoID NeXT®). MSIsensor was used to calculate percent unstable microsatellite loci from whole exome sequencing data. CIBERSORT and ssGSEA were used to analyze immune gene expression in relationship to percent unstable microsatellite loci. An immune checkpoint gene expression signature was calculated as the mean expression of CD274, CTLA-4, HAVCR2, LAG-3, PDCD1, PDCD1LG2, TIGIT. Aforementioned variables were analyzed in relationship to objective tumor response (RECIST version 1.1). A Cox proportional hazards model was fit to predict progression-free survival (PFS). Results: Among 32 patients with d-MMR mCRC treated with PD-1 blockade, 16 (50%) received first-line anti-PD-1 therapy; others had > 1 prior chemotherapy regimen. Eighteen (56.3%) tumors harbored BRAFV600E, 4 (12.5%) had mutant KRAS, and median PFS was 24.6 months (95% CI: 8.4, NR) with 18 events. Neither tumor mutation burden (TMB) nor PD-L1 mRNA expression predicted PFS. Median percent unstable MS loci was 14.38 (IQR: 2.6-23.2). Patients whose tumors had higher percent unstable MS loci had significantly better PFS (Q2-4 vs Q1; HR: 0.22, 95%CI: 0.06, 0.62; P=0.003), and were associated with increased objective response (P=0.049). Tumors with higher unstable loci also had higher neoantigen clonality (R= 0.64; P= 0.0003) and increased M0 (resting) macrophages (P=0.02). Nonresponders (vs responders) to PD-1 blockade had an increased immune checkpoint expression signature (P= 0.005). Conclusion: A higher percentage of unstable microsatellite loci, associated with higher neoantigen clonality and resting macrophages, was predictive of anti-PD-1 efficacy. Furthermore, an immune checkpoint gene expression signature was associated with objective response. Citation Format: Bahar Saberzadeh-Ardestani, Oluwadunni E. Emiloju, Rondell P. Graham, Jason T. Lewis, Charles W. Abbott, Sean M. Boyle, Frank A. Sinicrope. Prediction of PD-1 treatment outcome in mismatch repair deficient metastatic colorectal cancer using a multi-omic approach [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 578.

55 Background: Nearly one-half of deficient mismatch repair (d-MMR) metastatic colorectal cancers (mCRC) demonstrate durable responses to immune checkpoint inhibitors (ICIs). Given preclinical data indicating that liver metastases sequester activated CD8+ T cells from systemic circulation, we examined clinical outcome by metastatic site. Methods: In a retrospective cohort of patients with d-MMR mCRCs treated at multiple centers in France (n=66), we sought to validate data from a U.S. cohort, and then performed pooled analysis (n=104). All patients received first-line ICI monotherapy. Metastatic site was analyzed in relationship to tumor response (RECIST version 1.1), and progression-free survival (PFS) by multivariable stratified Cox regression after adjustment for covariates. Results: Objective responses were achieved in 38/66 (58%) patients in the validation cohort. Best tumor response included 13 (20%) complete responses (CR), 25 (38%) partial responses (PR), 16 (25%) stable disease, and 11 (17%) progressive disease (PD). One-year and 5-year PFS rates were 73% and 67%, respectively; 18 (27%) patients progressed during immunotherapy. Best tumor response was attenuated in patients with liver metastasis ( P=0.03). Presence of liver metastasis, but not other sites, was associated with significantly poorer PFS after adjustment for covariates (HRadj 2.82; 95%CI, 1.08-7.39; Padj=0.03). In a pooled analysis, liver metastasis remained significantly and independently associated with poorer PFS (HRadj 3.18; 95%CI, 1.52-6.67; Padj=0.002) and with attenuated tumor best response (P=0.01). Conclusions: Metastasis to the liver, but not other sites, was validated as an independent factor associated with poorer response and survival after ICI treatment in d-MMR mCRCs. These data underscore the need for novel therapeutic strategies in these patients. [Table: see text]

Abstract Purpose: Targeting the programmed cell death protein 1 (PD-1)/programmed cell death ligand 1 (PD-L1) interaction has led to durable responses in fewer than half of patients with mismatch repair–deficient (MMR-d) advanced colorectal cancers. Immune contexture, including spatial distribution of immune cells in the tumor microenvironment (TME), may predict immunotherapy outcome. Experimental Design: Immune contexture and spatial distribution, including cell-to-cell distance measurements, were analyzed by multiplex immunofluorescence (mIF) in primary colorectal cancers with d-MMR (N = 33) from patients treated with anti–PD-1 antibodies. By digital image analysis, density, ratio, intensity, and spatial distribution of PD-L1, PD-1, CD8, CD3, CD68, LAG3, TGFβR2, MHC-I, CD14, B2M, and pan-cytokeratin were computed. Feature selection was performed by regularized Cox regression with LASSO, and a proportional hazards model was fitted to predict progression-free survival (PFS). Results: For predicting survival among patients with MMR-d advanced colorectal cancer receiving PD-1 blockade, cell-to-cell distance measurements, but not cell densities or ratios, achieved statistical significance univariately. By multivariable feature selection, only mean number of PD-1+ cells within 10 μm of a PD-L1+ cell was significantly predictive of PFS. Dichotomization of this variable revealed that those with high versus low values had significantly prolonged PFS [median not reached (>83 months) vs. 8.5 months (95% confidence interval (95% CI), 4.7–NR)] with a median PFS of 28.4 months for all patients [adjusted HR (HRadj) = 0.14; 95% CI, 0.04–0.56; P = 0.005]. Expression of PD-1 was observed on CD8+ T cells; PD-L1 on CD3+ and CD8+ T lymphocytes, macrophages (CD68+), and tumor cells. Conclusions: In d-MMR colorectal cancers, PD-1+ to PD-L1+ receptor to ligand proximity is a potential predictive biomarker for the effectiveness of PD-1 blockade.

ImportanceThe incidence of early-onset colorectal cancer (CRC) (age, <50 years) continues to increase globally within high-income countries.ObjectiveTo examine and compare rates of synchronous neoplasia found in patients at colonoscopic diagnosis of early-onset CRC with rates found at diagnosis of average-onset CRC.Design, Setting, and ParticipantsIn this multisite retrospective and cross-sectional study conducted at Mayo Clinic sites and in the Mayo Clinic Health System from January 1, 2012, to December 31, 2022, 150 randomly selected patients with early-onset CRC were identified from the electronic health record and matched with 150 patients with average-onset CRC based on sex and colonoscopic indication. Patients with known hereditary syndromes, past history of CRC, or inflammatory bowel disease were excluded.Main Outcomes and MeasuresColonoscopic findings (polyp size, number, site) and related histopathologic findings (adenoma, advanced adenoma, sessile serrated polyp) were analyzed in association with cancer clinicopathologic features and molecular data (mismatch repair status, KRAS, and BRAFV600E).ResultsAmong 300 patients (156 men [52%]), the median age at diagnosis was 43 years (IQR, 39-47 years) for those with early-onset CRC and 67 years (IQR, 57-76) for those with average-onset CRC. Overall, 85% of patients were symptomatic at CRC diagnosis. Cancer stage, grade, molecular features, body mass index, and family history did not differ significantly between these groups. Among patients with colon cancer, the overall prevalence of synchronous neoplasia was similar, yet advanced adenomas were 3 times more frequent in those with early-onset vs average-onset cancers (31 of 75 [41%] vs 10 of 75 [13%]; P < .001). This difference was not associated with cancer stage or primary location. Among patients with rectal cancer, nonadvanced adenomas were less frequent among the early-onset group than the average-onset group (21 of 75 [28%] vs 36 of 75 [48%]), and although the prevalence of advanced adenomas was similar (11 of 75 [15%] vs 14 of 75 [19%]), they were more commonly located in the rectum (early onset, 5 of 11 [45%] vs average onset, 1 of 14 [7%]). Patients with early-onset cancer of the colon were significantly more likely than those with early-onset cancer of the rectum to have a synchronous advanced adenoma (31 of 75 [41%] vs 11 of 75 [15%]; P < .001).Conclusions and RelevanceIn this cross-sectional study, synchronous advanced adenomas were more commonly found in patients with early-onset colon cancer compared with average-onset colon cancer, and they were distributed throughout the colon. In contrast, advanced adenomas were not increased in patients with rectal cancer and, when detected, were predominantly located in the rectum.

Abstract Purpose: Microsatellite instability (MSI) is currently the only predictive biomarker of efficacy of immune checkpoint inhibitors (ICI) in metastatic colorectal cancers (mCRC). However, 10% to 40% of patients with MSI mCRC will experience a primary resistance to ICI. Experimental Design: In two cohorts of patients with MSI mCRC treated with ICI (exploratory, N = 103; validation, N = 35), 3′ RNA sequencing was performed from primary tumors. Previously described single-cell transcriptomic signatures of tumor microenvironment (TME) were analyzed. Results: In the exploratory cohort, the unsupervised clustering allowed the identification of three clusters of tumors with distinct transcriptional profiles: cluster A (“stromalHIGH-proliferationLOW”), cluster B (“stromalHIGH-proliferationMED”), and cluster C (“stromalLOW-proliferationHIGH”), with an enrichment of patients progressing at first disease assessment under ICI in cluster A (30% vs. 12% in cluster B and 8.1% in cluster C; P = 0.074). Progression-free survival (PFS) was also significantly shorter in patients belonging to cluster A, compared with clusters B or C (P < 0.001) with 2-year PFS rates of 33.5%, 80.5%, and 78.3%, respectively. In multivariate analysis, PFS was still significantly longer in patients belonging to cluster B [HR, 0.19; 95% confidence interval (CI), 0.08–0.45; P < 0.001] and cluster C (HR, 0.25; 95% CI, 0.10–0.59; P = 0.02), compared with patients belonging to cluster A. The association of this clustering with PFS under ICI was confirmed in the validation cohort. PFS related to non–ICI-based regimens was not significantly different according to cluster. Conclusions: This unsupervised transcriptomic classification identified three groups of MSI mCRCs with different compositions of TME cells and proliferative capacities of TME/tumor cells. The “stromalHIGH-proliferationLOW” cluster is associated with a poorer prognosis with ICI treatment.

3623 Background: Colorectal cancer (CRC) incidence has steadily increased in adults younger than 50 years (EO-CRC) since the 1990s, with a predominance in the left colon and rectum. Precursor lesions of CRCs are adenomas, including advanced adenomas, and sessile serrated polyps. Given that neoplastic development is age-related, we hypothesized that patients with early-onset CRC (EO-CRC) may have fewer adenomas compared to patients with average-onset CRC (AO-CRC) at diagnosis. Methods: We performed a retrospective review of electronic health records at Mayo Clinic or Mayo Health System [2012 to 2021] and randomly selected 150 patients with EO-CRC who met eligibility criteria and matched them with 150 AO-CRC patients based on gender and colonoscopy indication. Known hereditary syndromes or inflammatory bowel disease were excluded. At colonoscopy where CRC was diagnosed, we recorded findings of adenomas, advanced adenomas (> 1 cm, villous histology, or high-grade dysplasia), and sessile serrated polyps (SSP). Results: Median age at diagnosis was 43 years for EO-CRC and 67 years for AO-CRC. No significant differences in BMI, family history of CRC, MMR, BRAFV 600E KRAS status or SSPs were found between groups (all p > 0.05). Among patients with colon cancer, no difference was found for adenoma number yet patients with EO-colon cancer (EO-CC) had larger polyps [median of 10 mm vs 5 mm, p = 0.001] (Table) compared with AO-colon cancer (AO-CC). At least 1 adenoma was found in 56% and 47% of patients with EO-CC and AO-CC, respectively. Moreover, advanced adenomas were significantly more common in the EO-CC group compared with the AO-CC group (42% and 14%, p < 0.001) [ Table]. Among patients with rectal cancer, non-advanced adenomas were less frequent and although advanced adenoma were similar in frequency, they were more commonly located in the rectum in EO-rectal compared to AO-rectal cancers (Table). Conclusions: Patients with EO-colon cancer had a significantly higher likelihood of a synchronous advanced adenoma in the colon compared to those with AO-CRC. Together, these data suggest accelerated carcinogenesis throughout the colorectum in early onset patients, with increased risk for development of synchronous and metachronous CRC. [Table: see text]

3542 Background: Solid tumors can be characterized by distinct immune phenotypes based on the level of T cell infiltration in the tumor microenvironment (TME) which may provide prognostic information and also inform strategies to restore the anti-tumor immune response. Immune phenotypes were determined using an artificial intelligence (AI) algorithm in digitized whole-slide images (WSI) of tumors with deficient (d) mismatch repair (MMR) vs proficient (p) MMR. Methods: Stage III colon carcinomas (N = 401; 393 met QC) from participants in a phase III trial of FOLFOX-based adjuvant chemotherapy were analyzed including all available tumors with dMMR (n = 196) and a randomly selected cohort of pMMR tumors (n = 195). Using an AI algorithm (Lunit SCOPE) previously trained on solid tumors, digitized tumors were categorized into three immune phenotypes based on epithelial and stromal TIL data-driven cutpoints in dMMR and pMMR (inflamed: TIL high in epithelium (> upper 25%); excluded: TIL high in stroma (>lower 25%), low in epithelium; and desert: TIL low in epithelium and stroma). Phenotypes were then examined in relationship to disease-free survival (DFS) using Kaplan-Meier methodology. Results: Of the 3 immune phenotypes in dMMR tumors, 25% were inflamed, 50% were immune-excluded, and 25% were immune-desert. Based on univariate results, multivariable modeling was performed incorporating immune phenotype in addition to age, histological grade, N stage, T stage, performance status, treatment arm, BRAF and KRAS status and identified immune phenotypes and N stage to be significantly associated with DFS. Among dMMR tumors, immune desert phenotype was associated with the poorest DFS (Desert: HR adj 1.95, 95%CI (1.01, 3.80); Excluded: HR adj 0.89, 95%CI (0.47, 1.69); Inflamed: ref; p:0.01). When compared to immune desert tumors, immune-excluded tumors had significantly better DFS (HR adj 0.49, 95%CI (0.27, 0.88), p:0.01). At a median follow-up of 60 months, 3-year DFS of patients with dMMR was 71.2% with Immune inflamed, 78.5% with Excluded, and 54.5% with Desert phenotypes. In contrast to dMMR, univariate analyses of data-driven cutpoints in pMMR tumors was not prognostic. Using a different data-driven cutpoint (15%), the revised immune phenotypes remained non-significant for DFS within pMMR tumors. Conclusions: Distinct AI-derived immune phenotypes in the TME were identified that were significantly prognostic in patients with dMMR, but not pMMR colon cancers. A data-driven immune-desert phenotype was identified in dMMR tumors that was associated with significantly poorer survival. Further investigation of the potential predictive utility of these phenotypes for immunotherapy are planned. Support: https://acknowledgments.alliancefound.org . ClinicalTrials.gov Identifier: NCT00079274 .

3527 Background: Advances in deep learning may improve the ability to evaluate and quantify pathological features in solid tumors to improve prediction of patient disease-free survival (DFS). We used an artificial intelligence (AI) algorithm to quantify morphological features in the tumor microenvironment of stage III colon cancers. Methods: We analyzed digitized stage III colon carcinomas (N = 402; 382 met QC) from participants in a phase III trial of FOLFOX-based adjuvant chemotherapy that included all available tumors with dMMR and a randomly selected cohort of pMMR tumors (median follow-up 60 months) [NCCTG N0147; Alliance for Clinical Trials in Oncology]. Fifteen morphological features were extracted using the QuantCRC algorithm that segments images into carcinoma (low-grade, high-grade, signet ring cell), stroma (immature, mature, and inflammatory), mucin, tumor/stroma ratio, tumor budding/poorly differentiated clusters (TB/PDC), necrosis, smooth muscle, fat, and tumor-infiltrating lymphocytes (TILs) and tumor area (mucin, epithelium and TB/PDC). Analysis of AI-derived features with clinical variables, molecular alterations ( BRAF/KRAS), and DFS were examined using Kaplan-Meier methodology and multivariable Cox regression. Results: Among the 15 AI-derived morphological features, the following differed significantly between dMMR (n = 191) and pMMR (n = 189) whereby dMMR tumors had lower mature stroma, but higher inflammatory stroma and tumor, higher tumor grade and increased mucin, TB/PDCs, signet ring cells, and TILs (all p< 0.05). Among dMMR tumors, multivariable analysis revealed that tumor area [mucin, epithelium and TB/PDC] (HR adj 0.45, 95%CI (0.24, 0.84), p:0.01, [Q2/3 vs Q1]) and N stage were the only significant and independent prognostic variables. Among pMMR tumors, multivariable analysis identified that tumor budding/poorly differentiated clusters (TB/PDCs) (HR adj 0.20, 95%CI (0.06, 0.61), p:0.01, [Q1 vs Q4]) was the strongest prognostic variable and the only morphological feature that was significantly associated with DFS along with age, N stage and T stage. Conclusions: Using AI, we can extract and quantify distinct morphological features in tumor sections that differ between dMMR and pMMR and multivariately, can significantly and robustly enhance prognostication within each MMR group. Among pMMR tumors, tumor budding/poorly differentiated clusters was the strongest predictor of DFS. Support: NIH U10CA180821, U10CA180882, U24CA196171, R01 CA210509 (to FAS). Study NCCTG N0147 received funds from Sanofi https://acknowledgments.alliancefound.org . ClinicalTrials.gov Identifier: NCT00079274 Key words Artificial Intelligence; Tumor Microenvironment; Colonic Neoplasms; Disease-free survival.

Abstract Background: Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of patients with deficient DNA mismatch repair (d-MMR) metastatic colorectal cancer (CRC), yet less than half of patients receive clinical benefit. We hypothesized that immune contexture including spatial distribution of cells expressing immune molecules in the tumor microenvironment may predict immunotherapy outcome. Methods: Primary CRC tissues from consecutive patients with d-MMR metastatic CRC (N=33) were treated with anti-PD-1 antibodies at Mayo Clinic Comprehensive Cancer Center (2015-2018). Tumors were stained for PD-L1, PD-1, CD8, CD3, CD68, LAG3, TGFβR2, MHC-I, CD14, B2M, DAPI and pan-cytokeratin in 5 compartments (overall tumor, tumor epithelia, tumor stroma, peritumor inside vs outside) by multiplex immunofluorescence with digital image analysis. Features computed within each image analysis region included positive cell density, fraction of positive cell types, intensity of positive cells, and spatial distribution between distinct cell types (distances measured using image analysis software). Prior to model fitting, feature selection was performed using regularized Cox regression with LASSO. Regularization parameter was chosen based on 5-fold cross validation. A Cox proportional hazards model was fitted to predict patient progression-free survival (PFS). Results: Among patients with d-MMR CRCs, 16/33 (48.4%) were female, 10 received first-line ICI therapy, and 23 had received &gt; 1 prior chemotherapy regimen. Median age was 61.6 years (IQR of 49.4, 73.7). Eight patients (24.2%) harbored BRAFV600E, 9 (27.2%) had mutant KRAS, and median PFS was 22.2 months (95% CI: 11.8, NR) with 20 events. PD-L1 was expressed in tumor cells, CD68+ macrophages, and CD3+ T lymphocytes. PD-1 expression on CD8+ T lymphocytes was also observed. By univariate analysis, only cell-cell distance readouts achieved statistical significance. Multivariable feature selection identified the mean number of PD-1+ cells within 10 microns of a PD-L1+ cell in the overall tumor as the strongest predictor of anti-PD-1 efficacy, and was significantly associated with PFS (HR=0.87, 95% CI: 0.79-0.95, p&lt; 0.001). In contrast, the ratio of PD-1+/PD-L1+ cells was not predictive of treatment efficacy (p= 0.47), thereby underscoring the importance of spatial distribution for PFS prediction. Conclusion: The mean number of PD-1+ cells in proximity to PD-L1+ cells in tumors was a predictive biomarker of anti-PD-1 efficacy. Confirmatory studies are warranted. Citation Format: Bahar Saberzadeh-Ardestani, Rondell P. Graham, Qian Shi, Eze Ahanonu, Sara McMahon, Crystal Williams, Antony Hubbard, Wenjun Zhang, Andrea Muranyi, Dongyao Yan, Kandavel Shanmugam, Frank A. Sinicrope. Prediction of anti-PD-1 efficacy based on immune marker densities and their spatial distribution in colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6648.

Importance Metastatic colorectal cancer (mCRC) with deficient DNA mismatch repair (dMMR) shows frequent and durable responses to programmed cell death 1 blockade. While most of these tumors are sporadic and observed in older patients, first-line pembrolizumab data are limited to findings from the KEYNOTE-177 trial (A Phase III Study of Pembrolizumab [MK-3475] vs Chemotherapy in Microsatellite Instability-High [MSI-H] or Mismatch Repair Deficient [dMMR] Stage IV Colorectal Carcinoma). Objective To investigate outcome with first-line pembrolizumab monotherapy in mostly older patients with dMMR mCRC at a multisite clinical practice. Design, Setting, and Participants This cohort study included consecutive patients with dMMR mCRC who received pembrolizumab monotherapy between April 1, 2015, and January 1, 2022, at Mayo Clinic sites and the Mayo Clinic Health System. Patients were identified from review of electronic health records at the sites, which included the evaluation of digitized radiologic imaging studies. Intervention Patients with dMMR mCRC received first-line pembrolizumab, 200 mg, every 3 weeks. Main Outcomes and Measures The primary study end point was progression-free survival (PFS), which was analyzed using the Kaplan-Meier method and a multivariable stepwise Cox proportional hazards regression model. Clinicopathological features, including metastatic site and molecular data ( BRAF V600E and KRAS ), were also analyzed along with tumor response rate, which was determined using Response Evaluation Criteria in Solid Tumors, version 1.1. Results The study cohort included 41 patients (median [IQR] age at treatment initiation, 81 [76-86] years; 29 females [71%]) with dMMR mCRC. Of these patients, 30 (79%) had the BRAF V600E variant and 32 (80%) were classified as having sporadic tumors. Median (range) follow-up was 23 (3-89) months. Median (IQR) number of treatment cycles was 9 (4-20). Overall response rate was 49% (20 of 41 patients), including 13 patients (32%) with complete responses and 7 (17%) with partial responses. Median (IQR) PFS was 21 (95% CI, 6-39) months. Liver as a site of metastasis was associated with significantly poorer PFS vs nonliver metastasis (adjusted hazard ratio, 3.40; 95% CI, 1.27-9.13; adjusted P = .01). Complete and partial responses were observed in 3 patients (21%) with liver metastasis vs 17 patients (63%) with nonliver metastases. Treatment-related grade 3 or 4 adverse events were observed in 8 patients (20%), 2 of whom discontinued therapy; there was 1 treatment-related death. Conclusions and Relevance This cohort study found a clinically significant prolongation of survival in older patients with dMMR mCRC who were treated with first-line pembrolizumab in routine clinical practice. Furthermore, liver vs nonliver metastasis was associated with poorer survival in this patient population, which suggests that the metastatic site has implications for survival outcome.