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Colorectal cancer (CRC) is the third most common malignancy worldwide. It is projected to increase by 3.2 million new cases and account for 1.6 million deaths by 2040. Mortality is largely due to limited treatment options for patients who present with advanced disease. Thus, the development of effective and tolerable therapies is crucial. Chemotherapy has been the backbone of systemic treatment of advanced CRC, but utility has been limited because of invariable resistance to therapy, narrow mechanisms of action, and unfavorable toxicity profile. Tumors that are mismatch repair-deficient have demonstrated remarkable response to immune checkpoint inhibitor therapy. However, most CRC tumors are mismatch repair-proficient and represent an unmet medical need. Although ERBB2 amplification occurs only in a few cases, it is associated with left-sided tumors and a higher incidence of brain metastasis. Numerous combinations of HER2 inhibitors have demonstrated efficacy, and antibody-drug conjugates against HER2 represent innovative strategies in this area. The KRAS protein has been classically considered undruggable. Fortunately, new agents targeting KRAS G12C mutation represent a paradigm shift in the management of affected patients and could lead the advancement in drug development for the more common KRAS mutations. Furthermore, aberrant DNA damage response is present in 15%-20% of CRCs, and emerging innovative combinations with poly (ADP-ribose) polymerase (PARP) inhibitors could improve the current therapeutic landscape. Multiple novel biomarker-driven approaches in the management of patients with advanced CRC tumors are reviewed in this article.

e15510 Background: The SARS-CoV-2 (COVID-19) pandemic has had a lasting impact on the care of cancer patients. Multiple studies have shown that individuals with cancer are at high risk of serious complications in the setting of COVID-19 infection, but the impact in patients with gastrointestinal (GI) malignancies remain incompletely understood. We aimed to assess the impact of COVID-19 infection on mortality, length of stay (LOS), and cost of care among patients with GI malignancies, and identify differences in outcomes based on primary tumor site. Methods: We analyzed discharge encounters collected from the National Inpatient Sample (NIS) between March 2020 and December 2020, using propensity score-matching (PSM), and COVID- 19 as treatment effect. Results: Of the 87,684 patient discharges with GI malignancies, 1,892 were positive for COVID-19 (C+ve) and eligible for matching in the PSM model. Proportion for C+ve; male (61.2%), female (38.8%), White (55.8%), Black (17.9%), Hispanic (18.6%) and other (7.6%). Median age was 69 years (1QR: 61-77). Monthly variation reflected the wave and plateau dynamics of the spread of COVID-19. Following PSM analysis, C+ve patients with GI tumors demonstrated increased mortality compared to their COVID-19-negative (C-ve) counterparts (21.3% versus 11.9%, p < 0.001). C+ve patients with colorectal cancer (CRC) had significantly higher mortality compared to those who were C-ve; 39.95% [161/403] versus 24% [54/225], p = 0.035). In addition, C+ve patients with GI tumors had a longer LOS (9.42 days versus 6.95 days, p < 0.001) and increased cost of care ($26,048.29 versus $21,625.24, p = 0.001) compared to C-ve. Higher odds of mortality from myocardial infarction among C+ve(OR = 3.54, P = 0.001) while mortality due to pulmonary embolism or liver failure was not significantly different between C+ve and C-ve groups. Conclusions: This PSM analysis suggests that prior to the introduction of vaccines, C+ve patients with GI tumors faced approximately double the odds of mortality, an increased LOS of 2.5 days, and increased cost of care of about $4,400 compared to their C-ve counterparts. The disparity of outcomes was most pronounced among CRC patients. It is possible that the direct effects of the SARS-CoV-2 virus on the GI tract may predispose to mortality and disease severity, warranting further investigation. [Table: see text]

Triple negative breast cancer (TNBC) is the most aggressive molecular subtype of BC, with no targeted therapeutics currently available and poor systemic treatment response among certain patient groups. Cytokines, chemokines and adipokines are cell signaling molecules that play significant roles in mediation of inflammation/immune response in tumorigenesis and cancer progression. Relative systemic levels of these molecules secreted from the BC tumor microenvironment may be developed as prognostic liquid biopsy biomarkers. At present, we have investigated race-specific and TNBC-specific differences in circulating biomarker profiles of AA (n = 65) and EA (n = 88) BC patients. The International Center for the Study of Breast Cancer Subtypes (ICSBCS) maintains a prospective cohort biorepository of African and US patients, including patients from Detroit, MI (Henry Ford Health System) and New York City, NY (NewYork Presbyterian Hospitals). Using a multiplexed bead-based ELISA platform (Luminex®) we quantified the relative plasma levels of 45 different biomarkers per manufacturer’s protocols. Normalization of plate/batch effect was completed using MDimnNormn, and statistical tests were completed with JMP Pro 16. There were no significant differences between groups across most clinicopathological variables; including, age (p = 0.86), tumor histology (p = 0.45), subtype (p = 0.4039) or stage (p = 0.20). However, BMI was significantly higher among AA patients compared to EA patients (AA mean 31.5, EA mean 28.7, p = 0.016), and multivariate analyses were adjusted for BMI. Histological subtypes and stage represented a cross section of the cohort, with the majority being invasive ductal (AA 70.8%, EA 71.6%), and early-stage (Stage I and II) disease (AA 83.1%, EA 80.7%). The predominant intrinsic subtype is LumA (AA 69.2%, EA 67%), with a relatively higher proportion of TNBC disease among AA (20%) compared to EA patients (10.2%) (p = 0.086). Our univariate/unadjusted SRR-association models identified four biomarkers: IFNg (p = 0.022), I-TAC/CXCL11 (p = 0.003), MDC/CCL22 (p = 0.041) and MIPa/CCL3 (p = 0.038), which were higher among AA compared to EA patients. After controlling for BMI as a covariate in our model, all markers retained significance, with IFNg, I-TAC/CXCL11 and MIPa/CCL3 being p &lt; 0.05, and MDC/CCL22 with slightly lower significance (p = 0.054). To determine TNBC-specific profiles we compared biomarkers between TNBC (n = 22) and non-TNBC (n = 131) patients. The unadjusted/univariate analysis yielded no associations. However, after adjusting for BMI and SRR, 10 circulating biomarkers were significantly higher among patients with TNBC: IL16, MIF, TNFa, MPIF1/CCL23, IL1b, Gro-a/CXCL1, SCYB16/CXCL16, ENA-78/CXCL5, Fractalkine/CX3CL1 and Leptin (p &lt; 0.05). Taken together, these findings highlight that there are distinct SRR- and TNBC- circulating biomarker profiles, that may elucidate functional distinctions across TNBC patients to provide biomarkers for novel prognostic or therapeutic opportunities for patients. Citation Format: Rachel Martini, Millicent Amankwah, Julie Sahler, Brian Stonaker, Mumina Sadullozoda, Peter Radzio, Avery August, Lisa Newman, Melissa Davis. Race- and TNBC-specific circulating biomarker profiles among breast cancer patients [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr C009.

Background: The empirical dietary inflammatory pattern (EDIP) is a hypothesis-driven dietary pattern used to assess the inflammatory potential of diet in the US population. Food-frequency questionnaire responses are used to build regression models comparing this dietary information to circulating inflammatory profiles, to help determine which food groups have more or less inflammatory potential on specific individuals. We will eventually use this tool in a cancer patient intervention to modify inflammation and improve chances of survival. Methods: EDIP scores were calculated for 4 models from 24hr recalls reported by 67 women noncancer controls that had signed an informed consent prior to participation. The Luminex Human Chemokine Multiplex Assay was used to measure 11 chemokines and cytokines. As seen in previous studies, we first derived a model, EDIP-Limited (EDIP-L), by using a reduced rank regression model of all 17 food groups followed by a multivariable regression analysis to identify a dietary pattern that predicts concentrations of two inflammatory biomarkers: IL-6 and TNF-a. We derived a secondary EDIP score using a new model, EDIP-All Inclusive (EDIP-AI), which included the same 17 food groups to predict all 11 circulating biomarkers in our panel. Lastly, we developed two additional EDIP models to test how the biomarker predication may change when we regrouped our food variables from 17 to 14 groupings. EDIP-Limited New (EDIP-LN) used 14 new food groups derived from the same 24hr recalls, only predicting IL-6 and TNF-a. EDIP-All New (EDIP-AN) used those same 14 food groups with all 11 biomarkers. Results: In this study, we optimize models for EDIP and report the differences in EDIP scores based on the inflammatory biomarkers and food groups used in analysis. Briefly, the components of EDIP-L were not significant. After including all the biomarkers, the components of EDIP-AI were: “fruit juice” (p = 0.0009), “snacks” (p = 0.0008), “leafy green vegetables” (p = 0.0074), “low-energy beverages” (p = 0.0098), “red meat” (p = 0.0038), “fruit” (p = 0.0002) and “whole wheat grains” (p = 0.0138). Similarly, after reorganizing our food items into 14 food groups, the components of EDIP-LN were not significant. However, components of EDIP-AN were: “fruit juice” (p = 0.0107), “snacks” (p = 0.0116) and “fruit” (p = 0.0026). Conclusions: Findings demonstrate the EDIP scores differ based on the inflammatory biomarkers and food groups used in the analysis on the same noncancer controls. Depending on the methods used, an individual’s diet may be considered more pro- or anti-inflammatory. This study provides insight into the inflammatory potential of an individual’s diet and the factors that may affect how we calculate this potential.