Citations

Identifying risk factors for post-acute sequelae of COVID-19 (PASC) is important. We conducted a multicenter cross-sectional survey study to define and characterize risk factors for severe COVID-19 in adults (≥18 years) treated at our virtual COVID-19 clinic from March 1, 2020, through March 31, 2021. We assessed patient demographics, symptom types, and persistence, incidence of PASC, and COVID-19–caused hospitalizations. Surveyed patients were also asked to rate their perception of the severity of their acute COVID-19 symptoms. Continuous variables were summarized descriptively. Differences among groups categorized by acute COVID-19 symptom severity level (mild/very mild, moderate, and severe/very severe) were evaluated with the Kruskal–Wallis rank sum test for continuous measures and the Pearson χ 2 test for categorical measures. A total of 3094 adults completed the survey. More respondents with severe/very severe acute COVID-19 symptoms reported having PASC than did those with mild/very mild and moderate acute symptoms. A significantly greater proportion of respondents with PASC were women (68.4% vs 56.7%, p < 0.001), had been hospitalized (12.2% vs 4.4%, p < 0.001), reported having negative psychological COVID-19–related repercussions (39.9% vs 15.3%, p < 0.001), and required more than 1 month to resume normal activities (38.8% vs 12.9%, p < 0.001) than did those without PASC. These findings may improve our understanding of PASC and provide a framework for early recognition of and intervention for patients at higher risk for PASC. Further research is needed to understand the predictors of persistent symptoms after acute SARS-CoV-2 infection and the risk of PASC.

581 Background: Several studies have established the crucial role of preexisting immune response measured by tumor-infiltrating lymphocytes (TILs) in triple-negative breast cancer (TNBC). Emerging studies showed that not only the number of TILs but also the location of TILs is as critical. There are 3 distinct immune landscapes described based on the locations of TILs, namely immune enriched (IN), immune excluded (IE), and immune desert (ID), which are associated with outcomes in TNBC treated with immune-checkpoint inhibitors. Here we evaluated characteristics associated with each immune landscape. Methods: NanoString IO360, Digital Spatial Profiling (DSP), and CosMx, a spatial multi-omics single-cell imaging platform, were used. DSP was used to quantify 39 immune-related proteins in stromal and tumor-enriched segments from 44 TNBC samples from the FinXX trial (NCT00114816) and 276 samples from the Mayo Clinic (MC) TNBC cohort (Leon-Ferre BCRT 2018). CosMx was performed in 75 samples from the MC TNBC cohort. First, tumors with TIL quantified by H&E ≤ 30% were classified as ID. The rest of the tumors were categorized according to the intratumoral CD8 protein expression by DSP, with IE having intratumoral CD8 in the lower median and IN having intratumoral CD8 in the upper median. Differential expression listed as log fold change (FC) was estimated from the linear mixed model with significance defined as two-sided p < 0.05. Results: Using DSP in the FinXX trial, intratumoral and stromal higher HLA-DR (FC 1.68, p = 0.001), B2M (FC 0.8, p = 0.005), CD4 (FC 0.74, p = 0.01), and CD40 (FC 1.56, p = 0.001) were associated with IN compared to ID. When comparing IE and IN, higher intratumoral CD11c (FC 0.97, p = 0.01) and stromal CD4 (FC 0.89, p = 0.047), CD20 (FC 0.85, p = 0.016), CD40 (FC 0.95, p = 0.045), and CD27 (FC 0.84, p = 0.024) were associated with IN. Similar findings were observed in the MC cohort. Moreover, intratumoral NY-ESO-1 expression (FC 0.55, p = 0.03) was associated with IN. Using GSEA with IO360 in the FinXX trial, PI3K-Akt signaling was associated with ID compared to IN (p = 0.01). We further evaluated the differential gene expression in a spatially resolved manner using CosMx with single-cell sequencing in the MC cohort. Expressions of MHC class I and class II in tumor cells, including HLA-A, HLA-B, HLA-C, HLA-DRA, HLA-DRB1, HLA-DPA1, and HLA-E, were associated with IN compared to ID and IE. Conclusions: Using an in-depth analysis with spatially defined context, we identified characteristics associated with distinct immune landscapes in TNBC. Our study highlights the potential future implications of intratumoral MHC expression, CD40, and PI3K-AKT as biomarkers and therapeutic targets. Clinical trial information: NCT00114816 .

Abstract Background: The etiology of colorectal cancer is not fully understood. Methods: Using genetic variants and metabolomics data including 217 metabolites from the Framingham Heart Study (n = 1,357), we built genetic prediction models for circulating metabolites. Models with prediction R2 &gt; 0.01 (Nmetabolite = 58) were applied to predict levels of metabolites in two large consortia with a combined sample size of approximately 46,300 cases and 59,200 controls of European and approximately 21,700 cases and 47,400 controls of East Asian (EA) descent. Genetically predicted levels of metabolites were evaluated for their associations with colorectal cancer risk in logistic regressions within each racial group, after which the results were combined by meta-analysis. Results: Of the 58 metabolites tested, 24 metabolites were significantly associated with colorectal cancer risk [Benjamini–Hochberg FDR (BH-FDR) &lt; 0.05] in the European population (ORs ranged from 0.91 to 1.06; P values ranged from 0.02 to 6.4 × 10−8). Twenty one of the 24 associations were replicated in the EA population (ORs ranged from 0.26 to 1.69, BH-FDR &lt; 0.05). In addition, the genetically predicted levels of C16:0 cholesteryl ester was significantly associated with colorectal cancer risk in the EA population only (OREA: 1.94, 95% CI, 1.60−2.36, P = 2.6 × 10−11; OREUR: 1.01, 95% CI, 0.99−1.04, P = 0.3). Nineteen of the 25 metabolites were glycerophospholipids and triacylglycerols (TAG). Eighteen associations exhibited significant heterogeneity between the two racial groups (PEUR-EA-Het &lt; 0.005), which were more strongly associated in the EA population. This integrative study suggested a potential role of lipids, especially certain glycerophospholipids and TAGs, in the etiology of colorectal cancer. Conclusions: This study identified potential novel risk biomarkers for colorectal cancer by integrating genetics and circulating metabolomics data. Impact: The identified metabolites could be developed into new tools for risk assessment of colorectal cancer in both European and EA populations.

Abstract Background: The importance of the antitumor immune response in TNBC is well established. TNBC with higher TILs are less likely to recur and more responsive to systemic therapy. Likewise, PD-L1+ TNBC are more likely to benefit from chemoimmunotherapy. However, TNBC is highly heterogeneous. Of the TNBC molecular subtypes, LAR TNBC is less sensitive to systemic therapy, has lower TILs and lower rates of PD-L1 positivity. The role of other immune related proteins in LAR TNBC is not well established. Here, we evaluated differentially expressed (DE) immune related proteins in the stromal and intratumoral compartments of LAR vs non-LAR TNBC tumors. Methods: We used the Nanostring GeoMX DSP platform to quantitate 58 proteins within spatially distinct intraepithelial, cytokeratin (CK)-positive tumor segments and adjacent CK-negative/nuclei-positive stromal segments in 248 TNBC tumors included in a tissue microarray generated from a cohort of pts with centrally confirmed TNBC who underwent breast surgery without prior neoadjuvant therapy. A subset (n=111) underwent bulk tumor RNA sequencing and were classified as LAR or non-LAR TNBC. DE proteins were identified using a negative binomial generalized linear model (SNR&gt;2, p&lt;0.05). A targeted set of DE proteins was dichotomized at the 80th percentile. Results: Of 111 TNBC tumors, 17 (15%) were LAR and 94 (85%) non-LAR. Compared to non-LAR TNBC, pts with LAR TNBC were older (age ≥50: 82% vs 52%, p&lt;0.01), with tumors that were more often of apocrine histology (35% vs 0%, p &lt;0.01), grade 1-2 (24% vs 1%, p&lt;0.01), and had lower Ki67 (Ki67 ≤15: 24% vs 11%, p=0.06). Most tumors were T1-2 (94% vs 93%, p=0.82) and N0 (53% vs 62%, p=0.09), respectively. As expected, expression of most immune-related proteins was higher in the stromal vs the intratumoral compartment for both LAR and non-LAR TNBC. When focusing on the stromal compartment, expression of multiple immune related proteins was significantly lower in LAR compared to non-LAR TNBC, including the pan-leukocyte marker CD45 (log-2 fold change [log2FC]: 0.552, p=0.05), the macrophage marker CD14 (log2FC: 0.834, p=0.06), CD44 (lof2FC: 0.637, p=0.07), and the immune checkpoint proteins IDO1 (log2FC: 0.914, p=0.04), VISTA (log2FC: 0.471, p=0.07), ICOS (log2FC: 0.444, p=0.08), and STING (log2FC: 0.544, p=0.09). Proteins with expression levels too low for comparisons included PD-L1, LAG3, FOXP3 and BCL-2. When focusing on the intratumoral compartment, expression of most immune-related proteins was very low in both LAR and non-LAR TNBC. Like in the stromal compartment, CD45 expression was lower in LAR TNBC (log2FC: 0.78, p=0.02). Expression of the immune checkpoint B7-H3 was lower in LAR TNBC (log2FC: 0.737, p=0.02), while expression of the T cell marker CD127 was higher (log2FC: -0.528, p=0.34). With regards to relevant non-immune markers, expression of Ki67 was lower in LAR TNBC (log2FC: 0.5498, p=0.05), consistent with the clinical assay. Conclusion: In this ultra high-plex spatial analysis, we provide first insights into the differential expression at the protein level of several targetable immune checkpoint molecules in LAR vs non-LAR TNBC. The lower expression of several immune related proteins in LAR TNBC is consistent with the hypothesis that LAR TNBC exhibits a “cold” immune microenvironment compared to other TNBC subtypes, potentially rendering itself less susceptible to immunotherapy-based strategies. These data support the need to consider TNBC molecular subtypes in future evaluations of immune-based therapeutic approaches. Funding: This work was supported by NIH grant P50CA116201 to RLF, JMC, KRK, FJC, DZ, JNI, and MPG; BCRF grant 19-161 to EAT and NCATS grant CTSA KL2 TR002379 to RLF. The contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIH Citation Format: Roberto A Leon-Ferre, Jodi M. Carter, David M. Zahrieh, David W. Hillman, Saranya Chumsri, Yaohua Ma, Jennifer M. Kachergus, Xue Wang, Judy C. Boughey, Minetta C. Liu, James N. Ingle, Krishna R. Kalari, Jose C. Villasboas Bisneto, Fergus J. Couch, E. Aubrey Thompson, Matthew P. Goetz. Digital spatial profiling of immune-related proteins in luminal androgen receptor (LAR) vs non-LAR triple-negative breast cancer (TNBC) [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P1-04-01.

440 Background: Futibatinib, an irreversible FGFR1–4 inhibitor, is being investigated for the treatment of advanced intrahepatic cholangiocarcinoma (iCC) with FGFR2 fusions/rearrangements. We conducted an indirect treatment comparison to evaluate efficacy outcomes with futibatinib for advanced iCC patients from the FOENIX-CCA2 trial (NCT02052778) relative to published data for chemotherapy and FGFR inhibitors. Methods: A systematic literature review was conducted to identify clinical trials for FGFR inhibitors published 01/2015-02/2021, with additional targeted searches for chemotherapy data. A simulated treatment comparison was conducted using individual-level patient data from FOENIX-CCA2 and published aggregate data from comparator trials, applying regression models to adjust for between-trial differences in baseline characteristics. Population-adjusted Cox regression models were used for base case time-to-event outcomes (progression-free survival [PFS], overall survival [OS], duration of response [DOR]) and binomial-logistic regressions for binary outcomes (objective response rate [ORR]). Results: Two studies of FGFR inhibitors among previously treated patients with FGFR2 fusions/rearrangements were identified with sufficient data for analysis: FOENIX-CCA2 (n=103) and FIGHT-202 (n=107, pemigatinib). Two studies were identified for chemotherapy in this setting (an analysis of prior systemic therapy in the FIGHT-202 cohort [n=53] and a natural history study using a clinicogenomic database [n=71]). Comparisons of futibatinib with chemotherapy showed significantly lower risk of progression or death with futibatinib (table). Comparisons of futibatinib with pemigatinib showed similar outcomes between treatments (table), however, there was a numerical advantage for futibatinib in all efficacy parameters. Conclusions: Data suggest that futibatinib provides longer survival vs chemotherapy among previously treated advanced iCC patients with FGFR2 fusions/rearrangements. No statistically significant differences were observed in efficacy outcomes between futibatinib and pemigatinib, although numerical trends favored futibatinib. Molecular detail such as improved activity against co-mutated tumours and resistance mutations may explain such trends. [Table: see text]

AbstractBackgroundCoccygodynia is a painful condition of the tailbone that occurs more commonly in females. The association of coccyx pain with pelvic floor symptoms and the prevalence of coccyx pain in women with pelvic pain has not previously been reported.ObjectiveTo identify the prevalence of coccygodynia in women with pelvic pain and to describe the association of coccygodynia with pelvic floor examination findings and symptoms.DesignRetrospective cohort analysis.SettingTertiary medical institution.ParticipantsOne hundred twenty‐seven women presenting for outpatient pelvic floor physical therapy treatment who underwent vaginal and rectal pelvic floor examination.Main Outcome MeasuresPrevalence of coccygodynia, pain scores, association of coccygodynia with other comorbidities and diagnoses, and association of coccygodynia with physical examination findings.ResultsSixty‐three (49.6%) of 127 women with pelvic pain presented with coccygodynia and 64 (50.4%) did not. Women with coccygodynia had significantly higher rates of muscle spasm (50.8% vs. 31.2%, p = .025) higher visual analog scale pain scores (median 5 vs. 3, p = .014), higher rates of outlet dysfunction constipation (31.7% vs. 10.0%, p = .032), and higher rates of fibromyalgia (15.9% vs. 3.1%, p = .014). On pelvic examination, women with coccygodynia were significantly more likely to have sacrococcygeal joint hypomobility (65.1% vs. 14.1%, p < .001), coccygeus muscle spasm (77.8% vs. 17.2%, p < .001), anococcygeal ligament pain (63.5% vs. 9.4%, p < .001), external anal sphincter pain/spasm (33.3% vs. 13.1%, p < .001), and impaired pelvic floor muscle coordination (77.8% vs. 57.8%, p = .016).ConclusionsAlmost 50% of women seeking pelvic floor physical therapy for pelvic pain had coexisting coccygodynia. These women had higher pain scores, increased pelvic floor dysfunction, and significantly greater abnormal physical exam findings. This study demonstrates a strong link between coccygodynia, pelvic floor symptoms, and pelvic pain and highlights the importance of screening for and identifying coccyx pain when evaluating women with pelvic pain.

AbstractBackground:The role of methylation in pancreatic cancer risk remains unclear. We integrated genome and methylome data to identify CpG sites (CpG) with the genetically predicted methylation to be associated with pancreatic cancer risk. We also studied gene expression to understand the identified associations.Methods:Using genetic data and white blood cell methylation data from 1,595 subjects of European descent, we built genetic models to predict DNA methylation levels. After internal and external validation, we applied prediction models with satisfactory performance to the genetic data of 8,280 pancreatic cancer cases and 6,728 controls of European ancestry to investigate the associations of predicted methylation with pancreatic cancer risk. For associated CpGs, we compared their measured levels in pancreatic tumor versus benign tissue.Results:We identified 45 CpGs at nine loci showing an association with pancreatic cancer risk, including 15 CpGs showing an association independent from identified risk variants. We observed significant correlations between predicted methylation of 16 of the 45 CpGs and predicted expression of eight adjacent genes, of which six genes showed associations with pancreatic cancer risk. Of the 45 CpGs, we were able to compare measured methylation of 16 in pancreatic tumor versus benign pancreatic tissue. Of them, six showed differentiated methylation.Conclusions:We identified methylation biomarker candidates associated with pancreatic cancer using genetic instruments and added additional insights into the role of methylation in regulating gene expression in pancreatic cancer development.Impact:A comprehensive study using genetic instruments identifies 45 CpG sites at nine genomic loci for pancreatic cancer risk.

Abstract Cell fate conversion by overexpressing defined factors is a powerful tool in regenerative medicine. However, identifying key factors for cell fate conversion requires laborious experimental efforts; thus, many of such conversions have not been achieved yet. Nevertheless, cell fate conversions found in many published studies were incomplete as the expression of important gene sets could not be manipulated thoroughly. Therefore, the identification of master transcription factors for complete and efficient conversion is crucial to render this technology more applicable clinically. In the past decade, systematic analyses on various single-cell and bulk OMICs data have uncovered numerous gene regulatory mechanisms, and made it possible to predict master gene regulators during cell fate conversion. By virtue of the sparse structure of master transcription factors and the group structure of their simultaneous regulatory effects on the cell fate conversion process, this study introduces a novel computational method predicting master transcription factors based on group sparse optimization technique integrating data from multi-OMICs levels, which can be applicable to both single-cell and bulk OMICs data with a high tolerance of data sparsity. When it is compared with current prediction methods by cross-referencing published and validated master transcription factors, it possesses superior performance. In short, this method facilitates fast identification of key regulators, give raise to the possibility of higher successful conversion rate and in the hope of reducing experimental cost.