French, Amy J.

Background: Considering the pathophysiological importance of the intestine-passing microbiota, we hypothesized that the mutational and microbial profiles of colorectal cancer might gradually change along detailed anatomical locations and that these trends might differ by the age of diagnosis and the microsatellite instability (MSI) status. Methods: We assessed somatic mutations and selected bacterial species in colorectal carcinomas along the cecum, ascending colon, transverse colon, descending colon, sigmoid colon, and rectum, utilizing targeted sequencing data ( N = 5685) from the Genetics and Epidemiology of Colorectal Cancer Consortium and tissue microbial data ( N = 1389) from the Health Professionals Follow-up Study and Nurses’ Health Study. Results: There were decreasing trends from the cecum to rectum in the prevalence of gene mutations in the IGF/PI3K, receptor tyrosine kinase (RTK)/RAS, TGFB, and WNT signaling pathways (all P trend < 0.0001), as well as high levels of Bacteroides fragilis ( P trend < 0.0001) and high levels of Fusobacterium nucleatum ( P trend = 0.0029) (but not enterotoxigenic Bacteroides fragilis or pks+ Escherichia coli ). Conversely, TP53 pathway mutations showed an increasing cecum-to-rectum trend ( P trend < 0.0001). Similar to later-onset cases diagnosed at ages 50 years and older, in early-onset cases diagnosed under the age of 50 years, we found generally decreasing cecum-to-rectum trends of IGF/PI3K, RTK/RAS, TGFB, and WNT pathway mutations and an increasing cecum-to-rectum trend in TP53 pathway mutations. By contrast, the cecum-to-rectum prevalence-changing trends in IGF/PI3K, RTK/RAS, TGFB, and TP53 pathway mutations were present in non–MSI-high tumors but not in MSI-high tumors (all P interaction < 0.0052). Conclusion: Non–MSI-high colorectal cancers exhibited decreasing cecum-to-rectum trends of IGF/PI3K, RTK/RAS, and TGFB pathway mutations (and an increasing trend of TP53 pathway mutations), in contrast to MSI-high tumors that demonstrated no such trends. Our study highlights the importance of detailed colorectal subsite information combined with tumor molecular and microbial characteristics in colorectal cancer research.

Abstract Introduction: The intricate cellular structure is a constantly evolving environment where cells interact, communicate, and adapt to their surroundings. The fate, role, and actions of each cell are shaped by its specific location within the tissue. Therefore, studying the spatial proteome is crucial for gaining a deeper understanding of physiological or pathological processes. With significant advancements in microscopy and mass spectrometry, it has become feasible to explore the cellular proteome at low or even single cell numbers. However, spatial proteomics is an evolving field with scope for newer sample preparation and data analysis techniques. Our objective was to develop a sample preparation workflow for analyzing proteome from limited cells extracted from formalin fixed paraffin embedded (FFPE) tissue using laser capture microdissection (LCM). Methods: One hundred cells from the FFPE normal colon tissue were extracted by LCM and collected into an AFA-compatible 96-well plate. Decrosslinking was performed at 900C for 50 minutes followed by lysis in a buffer composed of 100 mM triethylammonium bicarbonate and 0.1% n-dodecyl-β-D-maltoside using adaptive focused acoustic (AFA) energetics in scanning mode for 5 minutes. After lysis, the proteins were digested using Trypsin/Lys-C mix using AFA energetics for 1 hour. The resulting peptides were acidified with trifluoroacetic acid and analyzed on a timsTOF Ultra 2 mass spectrometer coupled to a nanoElute 2 liquid chromatography system using a 15 cm (75 μm) IonOpticks column, in DDA-PASEF mode for a total run time of 34 minutes. The data were searched against the UniProt Human Reviewed protein database using MSFragger. Results: We utilized AFA energetics to extract and digest proteins from a limited number of cells isolated from FFPE tissue using LCM. This experiment was conducted with technical replicates to ensure accuracy and reliability. A total of 3,723 proteins were identified across the three replicates, with replicate 1 identifying 3,895 proteins, replicate 2 identifying 3,754 proteins, and replicate 3 identifying 3,519 proteins. In total, we identified 21,005 peptides, with replicate 1 identifying 22,896 peptides, replicate 2 identifying 22,377 peptides, and replicate 3 identifying 17,741 peptides from 100 colon cells. Notably, we observed a 70% overlap in the proteins identified across the three replicates, which highlights the reproducibility of the approach. Conclusion: The entire sample preparation process, after cell collection, was completed within a concise four-hour timeframe, demonstrating the efficiency of this methodology for analyzing protein profiles from small cell populations. Further, this approach is highly adaptable to automation and high-throughput applications. Its adaptability and scalability make it a promising strategy for spatial proteomics applications. Citation Format: Dong-Gi Mun, Kiran Mangalaparthi, Daigo Gunji, Amy J. French, Raghavendra Pasupuleti, Cristine Charlesworth, Sameer Vasantgadkar, DEB BHATTACHARYYA, Akhilesh Pandey. An AFA assisted workflow for mass-spectrometry based proteomics of FFPE samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 7657.

ABSTRACT Imaging mass spectrometry has made significant advancements in recent years owing to its ability to study the spatial localization and abundance of proteins, peptides, lipids, glycans, metabolites, and drugs. In this study, we employed an imaging mass spectrometry‐based workflow called MALDI‐IHC, which uses antibodies conjugated with photocleavable mass‐tags, to investigate the detection of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) along with pan‐cytokeratin in formalin‐fixed paraffin‐embedded (FFPE) sections from cases with breast cancer. The expression of ER, PR, and HER2 was consistent with the clinical diagnosis based on conventional immunohistochemistry, lacking signal in triple‐negative cases and concordant signals in the cases that were classified as ER+/PR+/HER2+, ER+/PR+/HER2−, and ER−/PR−/HER2+ groups, respectively. In addition, the potential utility of a seconday antibody‐based MALDI‐IHC approach for HER2 expression was evaluated. In agreement with immunohistochemistry results, HER2 expression co‐localized within tumor regions in a HER2+ breast cancer case, while no expression was observed in a HER2− case. Collectively, these results highlight the potential of imaging mass spectrometry‐based MALDI‐IHC workflow for multiplexed detection of proteins in clinically relevant tissue sections.

Abstract Background Physical activity is associated with lower colorectal cancer (CRC) risk, but its association with molecular subtypes defined by genetic and epigenetic alterations of the disease is unclear. Such information may enhance the understanding of the mechanisms related to the benefits of physical activity. Methods Pooled observational (cases: n = 5386; controls: n = 6798; studies n = 5) and genome-wide association data (cases: n = 8178; controls: n = 10 472; studies n = 5) were used. We used multivariable logistic regression models and Mendelian randomization to assess the association between physical activity and the risk of CRC subtypes defined by individual tumor markers (and marker combinations), namely microsatellite instability status, CpG island methylator phenotype status, and BRAF and KRAS mutations. We used case-only analysis to test for differences between molecular subtypes. We applied Bonferroni correction to account for multiple tests. Results In the pooled observational analysis, higher levels of physical activity were associated with lower CRC risk (Obs-per 1SD, odds ratio [OR] = 0.94, 95% confidence interval [CI] = 0.90 to 0.97), with an association that was stronger in males (Obs-per 1SD, OR = 0.91, 95% CI = 0.87 to 0.96) than in females (Obs-per 1SD, OR = 0.97, 95% CI = 0.91 to 1.03; Pinteraction = .04). Higher physical activity was associated with a lower risk of CRC across all molecular subtypes, especially in males. There was no difference in the associations by subtypes by pooled observational or Mendelian randomization analyses. The findings did not differ by study design, anatomical site, and early or late age onset of CRC. Conclusions Our findings suggest that physical activity is not differentially associated with the 4 major molecular subtypes involved in colorectal carcinogenesis, indicating that its benefits extend broadly across colorectal cancer pathogenesis.

Abstract Background: Waist circumference (WC) and its allometric counterpart, “a body shape index” (ABSI), are risk factors for colorectal cancer; however, it is uncertain whether associations with these body measurements are limited to specific molecular subtypes of the disease. Methods: Data from 2,772 colorectal cancer cases and 3,521 controls were pooled from four cohort studies within the Genetics and Epidemiology of Colorectal Cancer Consortium. Four molecular markers (BRAF mutation, KRAS mutation, CpG island methylator phenotype, and microsatellite instability) were analyzed individually and in combination (Jass types). Multivariable logistic and multinomial logistic models were used to assess the associations of WC and ABSI with overall colorectal cancer risk and, in case-only analyses, to evaluate heterogeneity by molecular subtype, respectively. Results: Higher WC (ORper 5 cm = 1.06, 95% confidence interval, 1.04–1.09) and ABSI (ORper 1-SD = 1.07, 95% confidence interval, 1.00–1.14) were associated with elevated colorectal cancer risk. There was no evidence of heterogeneity between the molecular subtypes. No difference was observed regarding the influence of WC and ABSI on the four major molecular markers in proximal colon, distal colon, and rectal cancers, as well as in early- and late-onset colorectal cancers. Associations did not differ in the Jass-type analysis. Conclusions: Higher WC and ABSI were associated with elevated colorectal cancer risk; however, they do not differentially influence all four major molecular mutations involved in colorectal carcinogenesis but underscore the importance of maintaining a healthy body weight in colorectal cancer prevention. Impact: The proposed results have potential utility in colorectal cancer prevention.

Abstract We used deep learning (DL) to predict multiple genetic biomarkers of colorectal cancer (CRC) from routine histopathology images, aiming to identify morphological changes associated with the mutational profile of tumors. A new Transformer-based prediction model was developed which can simultaneously predict multiple biomarkers from a single histopathology image. We compared the performance of the multi-target approach to conventional single-target models. We analyzed five patient cohorts from the Genetics and Epidemiology of CRC Consortium (GECCO) with colorectal cancer (N=1,385 patients). Our model was trained on an internal data set (N=739) to predict the presence of &gt;200 genetic alterations, focusing on genes with non-silent mutations and mutational signatures, which were assessed using targeted sequencing. We used a 7-fold cross validation and validated the model on an independent, external data set (N=646). Morphological features of microsatellite instability (MSI) are detectable by DL models in histopathology images, making MSI a potential confounding factor. Thus, we also assessed whether our model can predict genetic alterations regardless of MSI status, or whether the model identifies the MSI phenotype. For the majority of biomarkers, the multi-target transformer reached a higher prediction performance as measured by the mean Area Under the Receiver Operating Characteristic (AUROC) Curve and lower standard deviation than single-target DL models. For the external validation set, the mean AUROC of the multi-target versus the single-target model was 0.78 (+/- 0.01) versus 0.72 (+/- 0.06) for BRAF mutations, 0.88 (+/- 0.01) versus 0.86 (+/- 0.03) for hypermutation status, 0.94 (+/- 0.01) versus 0.91 (+/- 0.02) for MSI, 0.86 (+/- 0.01) versus 0.80 (+/- 0.05) for RNF43 mutations and 0.72 (+/- 0.02) versus 0.69 (+/- 0.05) for TP53 mutations, respectively. However, our analysis of the individual prediction scores suggests that the model does not identify the phenotype of the alterations themselves. Instead, the model seems to determine the status of specific genetic alterations based on their correlation with MSI. Consequently, biomarkers which are associated with microsatellite stability have prediction scores negatively correlated with predicted MSI scores. Conversely, biomarkers which are associated with MSI have prediction scores positively correlated with predicted MSI scores. Our results demonstrate potential benefits of multi-target DL models in improving the predictive power and efficacy of histology-based biomarker extraction compared to single-target DL models. However, our results crucially highlight the importance of considering potential confounders, such as MSI status in CRC, and emphasize the need for extensive analysis beyond AUROC in studies focusing on DL-based biomarker detection. Citation Format: Marco Gustav, Marko van Treeck, Zunamys I. Carrero, Chiara M. Loeffler, Nic G. Reitsam, Bruno Märkl, Asier Rabasco Meneghetti, Lisa A. Boardman, Amy J. French, Ellen L. Goode, Andrea Gsur, Stefanie Brezina, Marc J. Gunter, Neil Murphy, Paul Limburg, Stephen Thibodeau, Sebastian Foersch, Robert Steinfelder, Tabitha Harrison, Ulrike Peters, Amanda Phipps, Jakob N. Kather. Assessing microsatellite instability dominance in colorectal cancer phenotype: A multi-study initiative using multi-target transformers for genomic biomarker prediction [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 4924.

Abstract Background: The genotoxin colibactin causes a tumor single-base substitution (SBS) mutational signature, SBS88. It is unknown whether epidemiologic factors’ association with colorectal cancer risk and survival differs by SBS88. Methods: Within the Genetic Epidemiology of Colorectal Cancer Consortium and Colon Cancer Family Registry, we measured SBS88 in 4,308 microsatellite stable/microsatellite instability low tumors. Associations of epidemiologic factors with colorectal cancer risk by SBS88 were assessed using multinomial regression (N = 4,308 cases, 14,192 controls; cohort-only cases N = 1,911), and with colorectal cancer–specific survival using Cox proportional hazards regression (N = 3,465 cases). Results: 392 (9%) tumors were SBS88 positive. Among all cases, the highest quartile of fruit intake was associated with lower risk of SBS88-positive colorectal cancer than SBS88-negative colorectal cancer [odds ratio (OR) = 0.53, 95% confidence interval (CI) 0.37-0.76; OR = 0.75, 95% CI 0.66–0.85, respectively, Pheterogeneity = 0.047]. Among cohort studies, associations of body mass index (BMI), alcohol, and fruit intake with colorectal cancer risk differed by SBS88. BMI ≥30 kg/m2 was associated with worse colorectal cancer–specific survival among those SBS88-positive [hazard ratio (HR) = 3.40, 95% CI 1.47–7.84], but not among those SBS88-negative (HR = 0.97, 95% CI 0.78–1.21, Pheterogeneity = 0.066). Conclusions: Most epidemiologic factors did not differ by SBS88 for colorectal cancer risk or survival. Higher BMI may be associated with worse colorectal cancer–specific survival among those SBS88-positive; however, validation is needed in samples with whole-genome or whole-exome sequencing available. Impact: This study highlights the importance of identification of tumor phenotypes related to colorectal cancer and understanding potential heterogeneity for risk and survival.

Abstract Background: Colorectal cancer (CRC) incidence has increased in those 50 years or younger compared to older individuals in recent decades. While the intra-tumoral microbiome is a potent facilitator of tumorigenesis, the role of the microbiome in early onset (eo)CRC is unclear. Identification of the intra-tumoral microbiome may enhance prediction of adverse outcomes to improve survival of CRC overall age groups and eoCRC. Methods: We performed targeted sequencing of tumor and matched normal DNA samples from 3695 colorectal cancer cases within the Genetics and Colorectal Cancer Consortium (GECCO) and the Colon Cancer Family Registry (CCFR). Tumor DNA was extracted from formalin fixed paraffin embedded (FFPE) or fresh frozen tissue. Normal tissue DNA was extracted from blood or normal surrounding colorectal tissue. We designed probes for the bacterial pathogens enterotoxigenic Bacteroides fragilis (ETBF), polyketide synthase positive E. coli (pks+ EC), and Fusobacterium nucleatum (Fn). We used logistic regression to assess tumor-associated bacteria and clinical parameters, tumor molecular characteristics, and tumor stage adjusted for age, sex, and study and a Cox promotional hazard to assess association with CRC-specific survival, overall and in eoCRC, adjusted for age at diagnosis, sex, mutational burden, and microsatellite instability (MSI) and stratified baseline hazards by study. Survival data were available for 2357 and 308 patients, overall and in eoCRC, respectively. Results: The prevalence of different bacteria in tumors differed slightly overall vs. in eoCRC tumors: ETBF (5.2%, 6.3%), pks+ EC (12.9%, 14.8%), and Fn (10.4%, 8.2%). Overall, men had a lower probability of tumors with Fn (odds ratio (OR)=0.8, 95% confidence interval (CI)=0.64-0.99, p=0.04) but higher odds of tumors with pks+ EC (OR=1.38, CI=1.14-1.68, p=0.001), compared to women. The odds of prevalent Fn were higher for proximal vs distal tumors (OR=1.76, CI=1.38-2.26, p&lt;0.001), but there was no association between tumor site and pks+ EC or ETBF. MSI-high tumors were more likely to carry Fn (OR=2.79, CI=2.08-3.75, p&lt;0.001) and less likely to carry pks+ EC (OR=0.63, CI=0.44-0.88, p=0.008) when compared to patients with MSS tumors. In patients with non-hypermutated tumors, we observed that pks+ EC positive tumors were associated with better CRC-specific survival (HR=0.73, CI=0.57-0.93, p=0.01), whereas ETBF positive tumors (HR=1.99, CI=1,18-3.36,p=0.009) and Fn positive tumors (HR=1.33, CI=1.04-1.72, p=0.03) were associated with poorer survival. In eo-CRC patients, Fn positive status was associated with poorer survival (HR=2.4, CI= 1.056 - 5.492, p=0.026). Conclusions: We showed that the intra-tumoral microbiome differs in distribution across patient populations and patient survival over all age groups and, specifically, in eoCRC. Citation Format: Meredith A. Hullar, Keith R. Curtis, Tabitha Harrison, Yi Lin, Robert Steinfelder, Sonja I. Berndt, Daniel D. Buchanan, Andrew T. Chan, David A. Drew, Jane Figueiredo, Amy J. French, Tabitha A. Harrison, Mark A. Jenkins, Johannes Melaku, Victor Moreno, Tomotaka Ugai, Shuji Ogino, Conghui Qu, Chenxu Qu, Steven Thibodeau, Syed Zaidi, Amanda I. Phipps, Ulrike Peters, on behalf of GECCO and CCFR investigators. Evaluation of intra-tumoral pks+ E. coli, enterotoxigenic B. fragilis and Fusobacterium nucleatum, overall and in early onset disease, in colorectal cancer cases [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 3039.