Preoperative Strategies for Locally Advanced Colon Cancer.

OPINION STATEMENT: Neoadjuvant chemotherapy is safe for patients with locally advanced colon cancer (LACC). The FOxTROT trial demonstrated a reduction in residual and recurrent cancer at 2 years with neoadjuvant chemotherapy for patients with cT3-4 LACC. Preoperative chemotherapy should be avoided, if possible, for patients with dMMR LACC, as over 50% of dMMR cancers have no pathologic response. Early universal testing of MMR status is critical to selecting the appropriate neoadjuvant therapy. Concerns about CT staging of LACC have limited uptake of neoadjuvant chemotherapy, as approximately 25% of patients with cT3-T4 cancer on CT have low-risk stage II disease. Development of CT criteria for malignant nodes should reduce the risk of over-staging. A multidisciplinary approach is needed to identify patients for neoadjuvant therapy. Neoadjuvant immunotherapy is safe and results in dramatic pathologic responses in patients with dMMR LACC. Longer follow-up is needed to determine if the exceptionally high pathologic response rates observed will translate into long-term remission. Remarkably, neoadjuvant immunotherapy has been found to cause major pathologic responses in a subset of patients with pMMR LACC, indicating the potential to cure more patients with this common cancer. Patients with cT4 LACC, whether stage II or III, have a substantial risk of recurrence despite adjuvant fluoropyrimidine plus oxaliplatin chemotherapy. We recommend neoadjuvant systemic therapy for all patients with cT4b LACC (dMMR and pMMR). Features of T4b disease are routinely reported by radiology. We use three cycles of FOLFOX chemotherapy for patients with cT4b pMMR LACC, due to the high rate of compliance and improvement in residual and recurrent disease. Patients with cT4b dMMR LACC should receive neoadjuvant immunotherapy, if there are no contraindications. Clinical trials of neoadjuvant therapy for LACC are of great interest and should provide training for radiologists to identify eligible patients. Results are anticipated from multiple ongoing trials of neoadjuvant chemotherapy, immunotherapy, and targeted therapy for pMMR LACC and immunotherapy for dMMR LACC.

Referral, Uptake, and Outcome of Genetic Counseling and Testing in Patients With Early-Onset Colorectal Cancer.

BACKGROUND: The incidence of early-onset colorectal cancer (EOCRC) is rapidly increasing. Pathogenic germline variants (PGVs) are detected in 16% to 20% of patients who have EOCRC, highlighting a need for genetic counseling (GC) and multigene panel testing in these patients. We aimed to determine the rate of referral to GC and uptake and outcomes of germline testing in patients with EOCRC. METHODS: We conducted a retrospective cohort study of patients aged <50 years diagnosed with colorectal cancer (CRC) from 2010 to 2019 at Cleveland Clinic. Demographic data were extracted, including age, sex, self-reported race, and family history of CRC. The proportions of patients with GC referral and completion of GC and genetic testing were investigated, and genetic testing results were analyzed. Multivariable logistic regression analysis was conducted to identify factors independently associated with GC referral and uptake. RESULTS: A total of 791 patients with EOCRC (57% male and 43% female) were included; 62% were referred for GC, and of those who were referred, 79% completed a GC appointment and 77% underwent genetic testing. Of those who underwent testing, 21% had a PGV detected; 82% were in known CRC-associated genes, with those associated with Lynch syndrome and familial adenomatous polyposis the most common, and 11% were in other actionable genes. Referral to GC was positively associated with family history of CRC (odds ratio [OR], 2.11; 95% CI, 1.51-2.96) and more recent year of diagnosis (2010-2013 vs 2017-2019; OR, 5.36; 95% CI, 3.59-8.01) but negatively associated with older age at diagnosis (OR, 0.89; 95% CI, 0.86-0.92). CONCLUSIONS: Referral to GC for patients with EOCRC is increasing over time; however, even in recent years, almost 25% of patients were not referred for GC. We found that 1 in 5 patients with EOCRC carry actionable PGVs, highlighting the need for health systems to implement care pathways to optimize GC referral and testing in all patients with EOCRC.

Genomic Predictors Associated With Exceptional Response to Systemic Therapy in Advanced Pancreatic Cancer.

INTRODUCTION: Exceptional response to therapy is rare in patients with advanced pancreatic cancer. This study explored potential genomic differences between typical and exceptional responses that could confer more favorable biology. METHODS: We included exceptional responders and controls with advanced pancreatic cancer from Cleveland Clinic from April 2013 to August 2017. Exceptional responders were defined as patients with an overall survival of more than 18 months for metastatic disease and more than 24 months for locally advanced disease. Clinical data were obtained, and next-generation sequencing was performed. Statistical analyses comparing the 2 groups were performed using descriptive statistics, the Kaplan-Meier method, and the log-rank test. RESULTS: The study comprised 4 exceptional responders and 6 controls. Both groups were well balanced in age, sex, race, and treatment regimens. Exceptional responders had significantly fewer nonsynonymous mutations than controls (2.25 vs 5.17; P = .014). A mutation count of less than 3 was associated with significantly better progression-free survival (17.2 vs 2.3 months; P = .002) and overall survival (29.4 vs 4.6 months; P = .013). Tumor mutational burden did not differ between exceptional responders and controls (4.88 vs 5.70 mut/Mb; P = .39). CONCLUSION: A lower number of nonsynonymous mutations may correlate with exceptional outcomes in patients with pancreatic cancer. These findings should encourage future studies into genomic signatures of exceptional response.

Distinct intratumoral microbiome of young-onset and average-onset colorectal cancer.

BACKGROUND: The unexplained rise of young-onset CRC (yoCRC, age <50 years) is of concern. Evidence suggests that microbial dysbiosis may be a contributing factor, but the tumor microbial profile of yoCRC in comparison to average-onset CRC (aoCRC, age >60) has not been fully investigated. METHODS: 16S rRNA amplicon sequencing was performed in tumor and paired adjacent non-malignant fresh frozen tissue specimens prospectively collected from 136 yoCRC and 140 aoCRC patients. Phyloseq, microbiomeSeq, metagenomeSeq, and NetComi were utilized for bioinformatics analysis. Statistical tests included Fisher's exact test, ANOVA, PERMANOVA with Bonferroni correction, linear regression, and Wilcoxon test. p-value <0.05 was considered statistically significant. FINDINGS: yoCRC patients were more likely to have left-sided (72.8 vs. 54.3%), rectal (36.7% vs. 25%), and stage IV (28% vs. 15%) tumors. yoCRC tumors had significantly higher microbial alpha diversity (p = 1.5 × 10-5) and varied beta diversity (R2 = 0.31, p = 0.013) than aoCRC tumors. yoCRC tumors were enriched with Akkermansia and Bacteroides, whereas aoCRC tumors showed greater relative abundances of Bacillus, Staphylococcus, Listeria, Enterococcus, Pseudomonas, Fusobacterium, and Escherichia/Shigella. Akkermansia had a predominantly negative correlation with the microbial communities in yoCRC tumors. yoCRC and aoCRC tumors had distinct microbial profiles associated with tumor location, sidedness, stage, and obesity. Fusobacterium (R2 = -0.23, p = 0.001) and Akkermansia (R2 = 0.05, p = 0.001) abundance correlated with overall survival in yoCRC. INTERPRETATION: Our study provides a comprehensive understanding of the microbial perturbations in yoCRC tumors. We identify microbial candidates that may highlight a distinct pathogenesis of yoCRC and serve as preventive, diagnostic, and therapeutic targets. FUNDING: Sondra and Stephen Hardis Chair in Oncology Research (A.A.K.).

Molecular Differences With Therapeutic Implications in Early-Onset Compared With Average-Onset Biliary Tract Cancers.

PURPOSE: Early-onset biliary tract cancer (eoBTC) is among the fast-growing subset of early-onset cancers, yet little is known about its biology. We sought to identify novel molecular characteristics of eoBTC in relation to average-onset BTC (aoBTC) using a real-world multiomics data set. METHODS: The study comprised patients with BTC whose tumors underwent molecular analyses at Caris Life Sciences and were categorized by age (<50 years for eoBTC, ≥50 years for aoBTC). P values were adjusted for multiple testing and considered significant at Q < 0.05 (molecular comparisons) or Q < 0.25 (Gene Set Enrichment Analysis [GSEA]). Insurance claims data were used for survival analysis. RESULTS: The study included 5,587 patients with BTC (453 eoBTC, median age = 44 years and 5,134 aoBTC, median age = 68 years). FGFR2 fusion (15.7% in eoBTC v 5.9% in aoBTC) and NIPBL fusion (1.1% v 0%) were significantly more prevalent in eoBTC (both Q < 0.001). The interferon gamma-IFG score (fold change [FC], 1.1; Q = 0.01) and T-cell inflammation score (FC, 17.3; Q = 0.03) were significantly higher in aoBTC. On GSEA, angiogenesis was enriched in eoBTC (normalized enrichment score [NES] = 1.51; Q = 0.16), whereas IFG (NES = -1.58; Q = 0.06) and inflammatory response (NES = -1.46; Q = 0.18) were enriched in aoBTC. The median overall survival (OS) was 16.5 (eoBTC) versus 13.3 months (aoBTC), hazard ratio = 0.86, P = .004. The median OS by FGFR2 fusion (with fusion v without) was 21.7 versus 15.0 months (P = .47) for eoBTC and 18.6 versus 12.2 months (P < .001) for aoBTC. CONCLUSION: We identified crucial differences including higher prevalence of FGFR2 fusions in eoBTC and variations in immunotherapy-related markers. Better outcomes in eoBTC were affected by the FGFR2 fusion status. Our findings underscore the need for ensuring access to next-generation sequencing testing, including prompt identification of actionable targets.

Multi-omics machine learning to study host-microbiome interactions in early-onset colorectal cancer.

The incidence of early-onset colorectal cancer (eoCRC) is rising, and its pathogenesis is not completely understood. We hypothesized that machine learning utilizing paired tissue microbiome and plasma metabolome features could uncover distinct host-microbiome associations between eoCRC and average-onset CRC (aoCRC). Individuals with stages I-IV CRC (n = 64) were categorized as eoCRC (age ≤ 50, n = 20) or aoCRC (age ≥ 60, n = 44). Untargeted plasma metabolomics and 16S rRNA amplicon sequencing (microbiome analysis) of tumor tissue were performed. We fit DIABLO (Data Integration Analysis for Biomarker Discovery using Latent variable approaches for Omics studies) to construct a supervised machine-learning classifier using paired multi-omics (microbiome and metabolomics) data and identify associations unique to eoCRC. A differential association network analysis was also performed. Distinct clustering patterns emerged in multi-omic dimension reduction analysis. The metabolomics classifier achieved an AUC of 0.98, compared to AUC 0.61 for microbiome-based classifier. Circular correlation technique highlighted several key associations. Metabolites glycerol and pseudouridine (higher abundance in individuals with aoCRC) had negative correlations with Parasutterella, and Ruminococcaceae (higher abundance in individuals with eoCRC). Cholesterol and xylitol correlated negatively with Erysipelatoclostridium and Eubacterium, and showed a positive correlation with Acidovorax with higher abundance in individuals with eoCRC. Network analysis revealed different clustering patterns and associations for several metabolites e.g.: urea cycle metabolites and microbes such as Akkermansia. We show that multi-omics analysis can be utilized to study host-microbiome correlations in eoCRC and demonstrates promising biomarker potential of a metabolomics classifier. The distinct host-microbiome correlations for urea cycle in eoCRC may offer opportunities for therapeutic interventions.

Plasma metabolomic differences in early-onset compared to average-onset colorectal cancer.

Deleterious effects of environmental exposures may contribute to the rising incidence of early-onset colorectal cancer (eoCRC). We assessed the metabolomic differences between patients with eoCRC, average-onset CRC (aoCRC), and non-CRC controls, to understand pathogenic mechanisms. Patients with stage I-IV CRC and non-CRC controls were categorized based on age ≤ 50 years (eoCRC or young non-CRC controls) or  ≥ 60 years (aoCRC or older non-CRC controls). Differential metabolite abundance and metabolic pathway analyses were performed on plasma samples. Multivariate Cox proportional hazards modeling was used for survival analyses. All P values were adjusted for multiple testing (false discovery rate, FDR P < 0.15 considered significant). The study population comprised 170 patients with CRC (66 eoCRC and 104 aoCRC) and 49 non-CRC controls (34 young and 15 older). Citrate was differentially abundant in aoCRC vs. eoCRC in adjusted analysis (Odds Ratio = 21.8, FDR P = 0.04). Metabolic pathways altered in patients with aoCRC versus eoCRC included arginine biosynthesis, FDR P = 0.02; glyoxylate and dicarboxylate metabolism, FDR P = 0.005; citrate cycle, FDR P = 0.04; alanine, aspartate, and glutamate metabolism, FDR P = 0.01; glycine, serine, and threonine metabolism, FDR P = 0.14; and amino-acid t-RNA biosynthesis, FDR P = 0.01. 4-hydroxyhippuric acid was significantly associated with overall survival in all patients with CRC (Hazards ratio, HR = 0.4, 95% CI 0.3-0.7, FDR P = 0.05). We identified several unique metabolic alterations, particularly the significant differential abundance of citrate in aoCRC versus eoCRC. Arginine biosynthesis was the most enriched by the differentially altered metabolites. The findings hold promise in developing strategies for early detection and novel therapies.

Differences in Tumor-Associated T cell receptor repertoires between Early-Onset and Average-Onset colorectal cancer.

The incidence of colorectal cancer (CRC) among individuals younger than age 50 (early onset CRC; EOCRC) has substantially increased, yet the etiology and molecular mechanisms underlying this alarming rise remain unclear. We compared tumor-associated T cell repertoires between EOCRC and average-onset CRC (AOCRC) to uncover potentially unique immune microenvironment-related features by age of onset. Our discovery cohort included 242 patients who underwent surgical resection at Cleveland Clinic from 2000 to 2020. EOCRC was defined as age < 50 years at diagnosis (N = 126), and AOCRC as age ≥ 60 years (N = 116). T cell receptor (TCR) abundance and clonality were measured by immunosequencing of tumors. Logistic regression models were used to evaluate the associations between TCR repertoire features and age of onset, adjusting for sex, race, tumor location, and stage. Findings were replicated in 152 EOCRC and 1,984 AOCRC cases from the Molecular Epidemiology of Colorectal Cancer Study. EOCRC tumors had significantly higher TCR diversity compared to AOCRC tumors in the discovery cohort (Odds Ratio (OR):0.44, 95% Confidence Interval (CI):0.32-0.61, p < .0001). This association was also observed in the replication cohort (OR : 0.74, 95% CI : 0.62-0.89, p = .0013). No significant differences in TCR abundance were observed between EOCRC and AOCRC in either cohort. Higher TCR diversity, suggesting a more diverse intratumoral T cell response, is more frequently observed in EOCRC than AOCRC. Further studies are warranted to investigate the role of T cell diversity and the adaptive immune response more broadly in the etiology and outcomes of EOCRC.

Comparison of characteristics and outcomes of young-onset versus average onset pancreatico-biliary adenocarcinoma.

BACKGROUND: Young-onset gastrointestinal malignancies appear to be increasing in incidence. There are limited data on young-onset pancreaticobiliary adenocarcinoma (YO-PBA). METHODS: The study comprised patients with PBA (pancreatic adenocarcinoma, intra-, and extra-hepatic cholangiocarcinoma) and included in the National Cancer Database (NCDB) between 2004 and 2017. YO-PBA was defined as a diagnosis at age less than 50 years. Logistic regression to assess factors associated with YO-PBA status, and cox proportional hazards modeling to associate relevant factors with overall survival was performed. RESULTS: The study cohort comprised 360,764 patients, with 20,822 (5.8%) YO-PBA. YO-PBA was associated with (p-values<0.0001 for all): male sex (6.3% YO-male out of all male patients vs. 5.2% YO-female, OR 1.29, 95% CI 1.25-1.33), Black race (7.9% YO-Black vs. 5.0% YO-White, OR 1.72, 95% CI 1.64-1.80), lower income (6.4% YO-lowest household income based group vs. 5.5% highest, OR 1.08, 95% CI 1.03-1.13). YO-PBA were more likely to present with stage-IV disease (6.4% YO-Stage IV of all stage IV vs. 5.4% YO-Stage I-III, OR 1.25, 95% CI 1.21-1.29 p-value < 0.0001). Factors associated with overall survival (OS) in non-operable patients included-sex - male vs. female, HR 1.12 (95% CI 1.08-1.15); race - Black vs. White, HR 1.23 (95% CI 1.06-1.42); income group - lowest vs. highest, HR 1.33 (95% CI 1.27-1.39), and treatment center type - academic vs. nonacademic center, HR 0.87 (95% CI 0.85-0.90). CONCLUSIONS: Socioeconomic factors significantly impact incidence and outcomes for young-onset pancreaticobiliary adenocarcinoma (YO-PBA). More work is needed to help understand the mechanisms involved while addressing the disparities.

Racial disparities negatively impact outcomes in early-onset colorectal cancer independent of socioeconomic status.

BACKGROUND: The incidence of colorectal cancer (CRC) in patients under age 50 is rising for unclear reasons. We examined the effects of socioeconomic factors on outcomes for patients with early-onset CRC compared to late-onset CRC. METHODS: Patients with CRC from 2004 to 2015 in the National Cancer Database were included and categorized by age (under or over 50 years). Differences in demographic and socioeconomic factors, disease characteristics, and survival outcomes between early-onset versus late-onset CRC patients were assessed by Chi-squared test and Cox models. RESULTS: The study population included 1,061,204 patients, 108,058 (10.2%) of whom were under age 50. The proportion of patients diagnosed under age 50 increased over time: 9.4% in 2004-2006, 10.1% in 2007-2009, 10.5% in 2010-2012, and 10.7% in 2013-2015 (p < 0.0001). Early-onset CRC patients were more likely to be Black (15.1% vs. 11.3%) or Hispanic (8.6% vs. 4.6%) and to present with stage 4 disease (24.9% vs. 17.0%), p < 0.0001 for all. Black patients had the worst median OS (58.3 months) compared to White (67.0 months), Hispanic (91.6 months), or Asian (104.9 months) patients, p < 0.0001. Within the subgroup of early-onset CRC patients with private insurance, Black patients had worse OS compared to White patients, even in communities with higher income and education status. CONCLUSIONS: Early-onset CRC continues to increase. Patients with early-onset CRC are more likely to be Black or Hispanic and to present with stage 4 cancer. Early-onset Black patients showed worse OS compared to White patients in all income subgroups, even with private insurance.