Genomic Classifier Research Articles

Predicting Metastasis and Mortality Risk in Prostate biopsy using genomics and biopsy related factors

Abstract Introduction/Objective Prostate cancer, the most prevalent cancer among men, is diagnosed through biopsy, yet its predictive accuracy for metastasis and mortality risk remains limited. An approach to stratifying this risk is by combining biopsy data and genetics. The Decipher genomic classifier aids in estimating such risks. This study investigates the correlation between Decipher, biopsy-related factors, and the risk of prostate cancer metastasis or mortality. Methods/Case Report 50 prostatic adenocarcinoma biopsies were analyzed. Patient age, average tumor volume in positive cores, PSA levels, and Gleason score were documented. Employing Tobit regression with maximum likelihood estimation, the study examined the link between various factors and metastasis/mortality risk of prostatic cancer. Dependent variables encompassed 5, 10, and 15-year risks, while the independent variable was patient age, positive to total core ratio, average tumor volume in positive cores, PSA level, and grade group of the prostate cancer. The model integrated three dummy variables-Grade Group 1, 3, and 4, with Grade Group 2 as reference. Coefficients gauged the distinct impact of Level 1, 3, and 4 diagnoses on outcomes relative to Level 2. Statistical significance was tested conventionally. Results (if a Case Study enter NA) Grade Group 1 (Gleason score: 3 + 3): 2.35 percentage point increase in the risk of metastasis within 10 years. 3.51 percentage point increase in the risk of mortality within 15 years. Grade Group 2 Base level for comparison with other grade groups. Grade Group 3 (Gleason score: 4 + 3): No statistically significant difference in the predicting 5 or 10 year risk of metastasis compared to Grade Group 2. No statistically significant difference in the predicting 15 year risk of mortality compared to Grade Group 2. Grade Group 4 (Gleason score: 4 + 4): 10.07 percentage point increase in the risk of metastasis within 5 years. 17.27 percentage point increase in the risk of metastasis within 10 years. 18.48 percentage point increase in the risk of mortality within 15 years. Conclusion The findings suggest combining genomics and grade group can help predict the risk of metastasis and mortality in prostate biopsy. Grade Group 4 diagnosis greatly impacts metastasis and mortality in all timeframes.While Grade Group 1 has a smaller but still significant impact on the 10 and 15 year risk of metastasis and mortality. However, Grade Group 3 diagnosis does not significantly impact the risk of metastasis in any of the timeframes considered.

12351 Real World Performance of the Afirma Xpression Atlas in Bethesda V and Vi Thyroid Nodules: A Private Practice Experience

Abstract Disclosure: M.S. Tkach: None. E. Coughlin: None. A. Pinero-Pilona: None. Fine Needle Aspiration (FNA) is a cornerstone of the diagnosis of thyroid cancer. The Bethesda System for Reporting Thyroid Cytopathology (BS-TCP), developed in 2010, and genomic sequencing classifiers (GSC) now allow clinicians to objectively identify the risk of malignancy of thyroid nodules (“TN”) prior to surgical interventions. For further characterization, the Afirma Xpression Atlas (XA) was created and launched in May 2018, utilizing RNA sequencing to evaluate fusions and variants. As of 2023, the Afirma XA panel includes 905 genomic variants and 235 fusions from 593 genes. Post-validation studies for the Afirma XA have focused on large academic centers, but applicability or extrapolation to smaller endocrinology practices is less clear, potentially due to different patient population and thyroid cancer prevalence. This study was designed to analyze and measure the performance of the Afirma XA in BS-TCP V and VI TN classified as GSC suspicious for malignancy in a small endocrinology practice. We conducted a retrospective cohort analysis comparing all BS-TCP V and VI TN with their respective final surgical pathology results between June 2018 and December 2023. 76 TN meeting the criteria for BS-TCP V or VI classification were identified. We excluded any TN (12 total) for which pathology data was unavailable; reasons ranged from lack of patient follow-up to patient's death with no autopsy available. Forty-seven thyroid TN were therefore included, and the BS-TCP VI category was the predominant cytopathology discovered, representing 78.7% of the TN in this group. Afirma XA was able to identify genomic alterations in 78.7% of all included TN (thus 78.7% is its sensitivity). Sensitivity of XA was found to be 70% in BS-TCP V (n=10) and 81.1% in BS-TCP VI (n=37). 83% of the analyzed TN were from female patients and 17% were from male patients; there was no statistically significant difference between XA frequency in TN from male vs. female patients. 100% of all BS-TCP V and VI TN (n=47) as determined by the cytopathologist were associated with cancer on pathology; thus, the sensitivity of the cytopathology itself is 100%, and positive predictive value of XA in both groups was 100%. Age and nodule size were not significantly associated with XA presence or absence overall. XA was overwhelmingly comprised of BRAF :p:V600E c.1799T>A mutations: 70.2% of of XA findings showed this mutation (50% in V and 75.6% in VI). Our percentage of XA on BS-TCP V and VI nodules reflects similarity to prior large studies in academic centers. Based on this data, we conclude that XA is a valuable tool for high-risk TN classification and treatment guidance; it can both aid in surgical planning and determine options for potential pharmacotherapy. We conclude that in our study, the relation between XA and cytopathology in BS-TCP V and VI nodules correlates well with data from large academic center studies, even in a small private practice. Presentation: 6/3/2024

8172 Retrospective Analysis of mRNA Expression Based Signatures of Thyroid Tumor Invasion and Metastases

Abstract Disclosure: S. Ahmadi: None. E. Namiranian: None. M. Alshalalfa: Employee; Self; Veracyte, Inc.. Stock Owner; Self; Veracyte, Inc. R. Jiang: Employee; Self; Veracyte, Inc.. Stock Owner; Self; Veracyte, Inc. Y. Hao: Employee; Self; Veracyte, Inc.. Stock Owner; Self; Veracyte, Inc. J.P. Klopper: Employee; Self; Veracyte, Inc.. Stock Owner; Self; Veracyte, Inc. R.T. kloos: Employee; Self; Veracyte, Inc.. Stock Owner; Self; Veracyte, Inc.. E. Marqusee: None. The American Thyroid Association thyroid cancer risk stratification system is driven primarily by the extent of vascular and extrathyroidal extension, as well as lymph node metastases. Minimizing surgical intervention for thyroid tumors from indeterminate thyroid nodules (ITN - Bethesda III and IV cytology) is often preferred to mitigate surgical complications and lessen the need for thyroid hormone supplementation post-operatively if clinical outcomes are not worsened. By leveraging the whole transcriptome derived Afirma Genomic Sequencing Classifier (GSC) thyroid nodule molecular testing platform, mRNA expression-based signatures were developed to predict thyroid tumors with a low risk of clinically significant invasion and metastases with a > 95% negative predictive value as part of the Afirma Genomics Resource for Intelligent Discovery (GRID). The objective of this study was to analyze the performance of these signatures on a retrospective cohort of patients with ITN who had Afirma GSC suspicious findings and thyroid surgery. Two hundred three subjects were evaluated, and pathology reports were scored for the extent of thyroid tumor invasion or metastases. Tumors with extensive vascular invasion or extrathyroidal extension are labeled as high risk (and otherwise are low risk). Tumors with lymph node metastases that either have documented > 2mm tumor deposits, > 40% of central nodes involved, or lateral lymph node metastases are labeled as high risk (and otherwise are low risk). The Afirma GRID invasion and metastases signatures were applied to correlate with the pathology scoring. The cohort was comprised of 144 (70%) female and 59 (30%) male patients with median age of 54 [IQR 40-65]. The cohort was mostly Bethesda III (n= 152, 75%). Fifty three percent (n=109) of the samples were malignant upon histology review. Two samples were scored as high risk for lymph node metastases (LNM) and 4 samples were scored as high risk for invasion (INV) based on final pathology. The LNM signature ruled out 55% of samples with 100% NPV and 55% specificity. No samples with high risk LNM scores were erroneously ruled out by the LNM GRID signature. The rule out % was similar in female (58%) and males (46%) (chi-squared test p=0.1). For the invasion model, 57% of samples were ruled out with 99% NPV and 57% specificity. One sample with extra-thyroidal invasion had a false negative GRID INV signature. The INV rule out % was similar in female (57%) and males (54%) (chi-squared test p=0.19). In summary, the Afirma GRID INV and LNM signatures ruled out clinically significant thyroid tumor features in > 50% of the studied cohort with > 95% NPV. Prospective studies should be performed to confirm the potential for Afirma GRID tumor behavior signatures to optimize and individualize surgical decision-making, decreasing the burden of unnecessary extent of thyroid surgery while maintaining outstanding clinical outcomes. Presentation: 6/3/2024

8109 Cancer-Associated Fibroblasts Correlate with Aggressive Thyroid Cancer Behavior: Insights from Four Large Patient Cohorts

Abstract Disclosure: M.A. Loberg: None. X. George: None. P.J. Courtney: None. H.C. Eric: None. A. Golding: None. B. David: None. M. Alshalalfa: Employee; Self; Veracyte, Inc.. Stock Owner; Self; Veracyte, Inc. Y. Hao: Employee; Self; Veracyte, Inc.. Stock Owner; Self; Veracyte, Inc. J.P. Klopper: Employee; Self; Veracyte, Inc.. Stock Owner; Self; Veracyte, Inc. R.T. Kloos: Employee; Self; Veracyte, Inc.. Stock Owner; Self; Veracyte, Inc.. V. Weiss: None. Thyroid tumor molecular analysis often utilizes fine-needle aspirate (FNA) samples to predict malignancy with high sensitivity. An outstanding question is if molecular sequencing can provide prognostic information to predict disease aggression, potentially informing management. Recently, the composition of the tumor microenvironment, in particular the presence of tumor-promoting fibroblasts, has been associated with aggressive thyroid cancer. However, fibroblast gene expression has not previously been analyzed in thyroid tumor FNA samples. In this work, we detect cancer-associated fibroblast (CAF) gene signatures across 4 distinct bulk RNA sequencing cohorts and confirm detection in FNA samples. Associations between CAF gene signatures and tumor characteristics were explored in: Afirma Genomic Sequencing Classifier (GSC) cohort from FNA (n=47,695), a Memorial Healthcare System (MHS) retrospective FNA cohort with pathology outcome data (n=318), TCGA papillary thyroid cancers (n=496), and a Vanderbilt University Medical Center-University of Washington (VUMC-UW) resection cohort (n=312). Published breast CAF gene sets were used to generate normal fibroblast and CAF subtype scores. Novel thyroid cancer specific CAF gene sets were generated from thyroid cancer single-cell RNA sequencing data. Scores for each gene set were calculated as the average Z-score. Across all cohorts, multiple CAF subsets were enriched in samples with BRAFV600E and papillary histology. The strongest enrichment was in an SFRP2+ CAF subset identified in thyroid cancer single-cell sequencing data. In Afirma GSC FNA samples, SFRP2+ CAFs were enriched in GSC-suspicious and Bethesda V/VI relative to GSC-benign nodules (Wilcoxon p value < 2e-[1]6 for all). In TCGA, SFRP2+ CAFs were associated with extrathyroidal extension, advanced disease stage, and aggressive histology. In the MHS cohort of 318 malignant FNA samples, SFRP2+ CAFs were significantly higher in patients with vascular invasion or lymph node metastasis (LNM) (OR:2.75 [95% CI 1.63-4.75], p=4e-5). In the VUMC-UW cohort, SFRP2+ CAFs were associated with shorter progression-free survival (PFS) (p=0.0033). In summary we created a novel thyroid cancer-specific CAF gene signature that is elevated in BRAFV600E+ and aggressive thyroid cancers across multiple large patient cohorts. We also demonstrated the ability to detect these CAF signatures in thyroid FNAs using the Afirma GSC molecular testing platform, with enrichment in suspicious and malignant samples. Amongst the CAF scores tested, thyroid-specific CAF subsets had the highest prognostic potential, and SFRP2+ CAFs, specifically, were associated with shorter PFS, tumor invasion and LNM. Together, these results highlight the potential of interrogating the thyroid tumor stroma in FNA using RNA-based assays to inform prognosis and possibly management. Presentation: 6/3/2024

6913 Clinical Prognosis in Patients with Thyroid Nodules Expressing PPAR-Gamma Gene Fusion on Thyroid FNA Cytology

Abstract Disclosure: R. Hammoudeh: None. E. Morariu: None. A. Wald: Other; Self; Technical consultant to Sonic Healthcare USA.. W.R. Doerfler: None. Y. Linwah: None. M. Nikiforova: Owner/Co-Owner; Self; Owner of intellectual property related to ThyroSeq, receive royalties through the University of Pittsburgh; consultants for Sonic Healthcare USA. Y.E. Nikiforov: Owner/Co-Owner; Self; Owner of intellectual property related to ThyroSeq, receive royalties through the University of Pittsburgh; consultants for Sonic Healthcare USA. Background: PPARG rearrangements, typically PAX8-PPARG, are common genetic alterations in follicular thyroid carcinoma and follicular variant of papillary thyroid carcinoma (FVPTC). Most tumors appear to be indolent, however distant metastasis has been reported. The aim of this study was to determine the prevalence and type of malignancy in a series of thyroid nodules positive for PAX8 rearrangement in thyroid fine-needle aspiration (FNA) samples. We also aimed to evaluate the impact on patient management, prognosis and outcomes. Methods: Thyroid nodules positive for PAX8 fusion on ThyroSeq v2 and v3 genomic classifier testing of FNA samples from May 2008 to February 2022 were identified. Clinical data was obtained by retrospective chart review. Results: Overall, 44 nodules positive for PAX8/PPARG fusion were identified. None of these nodules expressed additional genetic mutations on molecular testing. Surgical pathology was available for 40 patients, which identified 35 (87.5%) malignant, 3 NIFTP (7.5%), and 2 benign (5%) lesions. In the malignant group, FNA cytology revealed 1 (2.8%) benign, 13 (37.1%) AUS/FLUS, 12 (34.2%) suspicious for SFN/FN, 5 (14.3%) suspicious for PTC and 4 were not classified. In the non-malignant group, FNA cytology revealed 2 (40%) benign, 2 (40%) AUS/FLUS, 1 (20%) SFN/FN. With regards to surgical intervention, 30 (75%) patients had total thyroidectomy and 10 (25%) underwent lobectomy, of which 8 were followed by completion thyroidectomy. Among the malignant and non-malignant groups, there was no difference in sex (82.8% vs 100% female, p=1), age (43.6 vs 50.2 years, p=0.2), or tumor size on surgical pathology (3.26 vs 4 cm, p=0.23). In the malignant group, histology showed 30 (85.7%) FVPTC, 2 (5.7%) conventional PTC, 2 (5.7%) follicular carcinoma and 1 (2.9%) solid variant PTC. Of the FVPTC group, 9 had oncocytic cell features, 3 focal solid patterns, and 1 showed focal solid growth and progression to poorly differentiated thyroid carcinoma. Only 1 showed lymphatic invasion, 10 showed angioinvasion. Following the ATA thyroid cancer risk stratification, 23 (65.7%%) had low risk, 9 (25.7%) intermediate risk and 3 (8.6%) high risk. 18 patients in the malignant group underwent RAI ablation. Average follow up for the malignant nodules was 49.7 months (0-170). 1 had suspected recurrence on thyroid ultrasound after a year. No evidence of distant metastasis was documented. Conclusions: The majority of thyroid nodules with PAX8/PPARG rearrangement found on FNA were cancers, predominantly follicular variant PTC, and some were benign or NIFTP. The majority were low risk, but intermediate and high-risk cancers with more aggressive histology, angioinvasion, and poorly differentiated cancer were also identified. While only one recurrence was identified on short follow-up, longer follow-up duration is required for better understanding the behavior of these tumors. Presentation: 6/3/2024

Genome-Derived Ampullary Adenocarcinoma Classifier and Postresection Prognostication

Ampullary adenocarcinoma (AA) is characterized by clinical and genomic heterogeneity. A previously developed genomic classifier defined biologically distinct phenotypes with greater accuracy than standard histologic classification. External validation is needed before routine clinical use. To test external validity of the prognostic value of the hidden genome classifier of AA. This retrospective cohort study took place at 6 international academic institutions. Consecutive patients (n = 192) who underwent curative-intent resection of histologically confirmed AA were included. The data were analyzed from January 2005 through July 2020. The multilevel meta-feature regression model previously trained on a prospectively sequenced cohort of 3411 patients (1001 pancreatic adenocarcinoma, 165 distal bile duct adenocarcinoma, and 2245 colorectal adenocarcinoma) was applied to AA sequencing data to quantify the relative proportions of parental cell of origin. Genomic classification was correlated with immunohistologic subtype (intestinal [INT] or pancreatobiliary [PB]) and with overall survival (OS), using the log-rank test and Cox proportional hazard models. Among 192 patients with AA (median age, 69.0 [IQR, 60.0-74.0] years and 134 were male [64%]), concordance between immunohistologic and genomic subtypes was 55%. Most INT subtype tumors were categorized into the colorectal genomic subtype (43 of 57 [72.9%]). Of the 114 PB subtype tumors, 29 had a pancreatic genomic profile (25.4%) and 24 had a distal bile duct genomic profile (21.1%). Whereas the standard immunohistologic subtypes were not associated with survival (log rank P = .26), predicted genomic probabilities were correlated with survival probability. Genomic scores with higher colorectal probability were associated with higher survival probability; higher pancreatic and distal bile duct probabilities were associated with lower survival probability. The AA genomic classifier is reproducible with available molecular testing in a diverse international cohort of patients and improves stratification of the divergent clinical outcomes beyond standard immunohistologic classification. These data provide a molecular classification that may be incorporated into clinical trials for prospective validation.

9 Delving into molecular underpinnings of sarcomatoid/rhabdoid dedifferentioation in renal cancers using spatial profiling

Abstract Background Renal cell carcinomas (RCC) are characterized by their largely diverse clinical outcomes. Leveraging genomic diversity among individual tumors, our research during the past decade has concentrated on developing personalized medicine approaches for the most common and the most aggressive type of RCC, clear cell renal carcinoma (ccRCC). We generated the largest dataset of ccRCC including somatic genomic and clinical annotations for over 940 ccRCC patients, and developed a genomic classifier, based on mutational status of 12 RCC-relevant genes, which is able to stratify patients according to their risk of relapse after nephrectomy and/or death due to RCC. Furthermore, we noticed the presence of mesenchymal-like cellular phenotypes in tumors of high-risk patients, representsing a de-differentiation process, known as sarcomatoic or rhabdoid (S/R) de-differentation. Methods The current knowledge about molecular mechanisms that may drive S/R de-differentiation is primarily generated from molecular profiling of bulk tumors, collecting data from a mixture of cells that co-exist in the tumor milieu. Therefore, high-resolution studies that precisely define molecular characteristics of different cellular phenotypes associated with S/R features are missing. We have used spatial transcriptomic profiling to investigate molecular mechanisms that underline S/R de-differentationin RCC. While preserving tissue context, we applied spatial whole human transcriptome profiling to areas exhibiting S/R or clear cell phenotypes within the same tumor specimens to generate phenotype-specific transcriptome profiles. In addition, we applied whole-exome sequencing (WES) to independent areas that exhibit different differentiation phenotype withing same tumors. Results Pathway and network analysis of genesets with upregulation in each area have revealed meaningful differences in cellular pathways which are active in each phenotype. Specifically, we observed that dysregulation of extracellular matrix (ECM) is a hallmark of S/R areas within RCC tumors. Furthermore, WES of phenotypically-distinct areas within each tumor has shed new light son the genome evoltuion of S/R phenotypes. Conclusions S/R dedifferentiation in RCC tumors is characterized by specific genomic evolutionary patterns and substantial dysregulation of ECM components. DOD CDMRP Funding: yes

Reporting tumor genomic test results to SEER registries via linkages.

Precision medicine has become a mainstay of cancer care in recent years. The National Cancer Institute (NCI) Surveillance, Epidemiology, and End Results (SEER) Program has been an authoritative source of cancer statistics and data since 1973. However, tumor genomic information has not been adequately captured in the cancer surveillance data, which impedes population-based research on molecular subtypes. To address this, the SEER Program has developed and implemented a centralized process to link SEER registries' tumor cases with genomic test results that are provided by molecular laboratories to the registries. Data linkages were carried out following operating procedures for centralized linkages established by the SEER Program. The linkages used Match*Pro, a probabilistic linkage software, and were facilitated by the registries' trusted third party (an honest broker). The SEER registries provide to NCI limited datasets that undergo preliminary evaluation prior to their release to the research community. Recently conducted genomic linkages included OncotypeDX Breast Recurrence Score, OncotypeDX Breast Ductal Carcinoma in Situ, OncotypeDX Genomic Prostate Score, Decipher Prostate Genomic Classifier, DecisionDX Uveal Melanoma, DecisionDX Preferentially Expressed Antigen in Melanoma, DecisionDX Melanoma, and germline tests results in Georgia and California SEER registries. The linkages of cancer cases from SEER registries with genomic test results obtained from molecular laboratories offer an effective approach for data collection in cancer surveillance. By providing de-identified data to the research community, the NCI's SEER Program enables scientists to investigate numerous research inquiries.

A Novel Approach to Quantify Heterogeneity of Intrahepatic Cholangiocarcinoma: The Hidden-Genome Classifier.

Intrahepatic cholangiocarcinoma (IHC) is a heterogeneous tumor. The hidden-genome classifier, a supervised machine learning-based algorithm, was used to quantify tumor heterogeneity and improve classification. A retrospective review of 1,370 patients with IHC, extrahepatic cholangiocarcinoma (EHC), gallbladder cancer (GBC), hepatocellular carcinoma (HCC), or biphenotypic tumors was conducted. A hidden-genome model classified 527 IHC based on genetic similarity to EHC/GBC or HCC. Genetic, histologic, and clinical data were correlated. In this study, 410 IHC (78%) had >50% genetic homology with EHC/GBC; 122 (23%) had >90% homology ("biliary class"), characterized by alterations of KRAS, SMAD4, and CDKN2A loss; 117 IHC (22%) had >50% genetic homology with HCC; and 30 (5.7%) had >90% homology ("HCC class"), characterized by TERT alterations. Patients with biliary- versus non-biliary-class IHC had median overall survival (OS) of 1 year (95% CI, 0.77, 1.5) versus 1.8 years (95% CI, 1.6, 2.0) for unresectable disease and 2.4 years (95% CI, 2.1, NR) versus 5.1 years (95% CI, 4.8, 6.9) for resectable disease. Large-duct IHC (n = 28) was more common in the biliary class (n = 27); the HCC class was composed mostly of small-duct IHC (64%, P = 0.02). The hidden genomic classifier predicted OS independent of FGFR2 and IDH1 alterations. By contrast, the histology subtype did not predict OS. IHC genetics form a spectrum with worse OS for tumors genetically aligned with EHC/GBC. The classifier proved superior to histologic subtypes for predicting OS independent of FGFR2 and IDH1 alterations. These results may explain the differential treatment responses seen in IHC and may direct therapy by helping stratify patients in future clinical trials.

Transcriptomic Profiling of Primary Prostate Cancers and Nonlocalized Disease on Prostate-Specific Membrane Antigen Positron Emission Tomography/Computed Tomography: A Multicenter Retrospective Study.

To characterize the relationship between Decipher genomic classifier scores and prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT)-based metastatic spread. We identified patients from four institutions who underwent PSMA PET/CT scans pretreatment for primary staging or postradical prostatectomy (RP) for suspected recurrence and had Decipher transcriptomic data available from biopsy or RP specimens. PSMA PET/CT-based patterns of spread were classified as localized (miT + N0M0) or nonlocalized (miN1M0 or miM1a-c). We calculated the association between Decipher scores and the risk of nonlocalized disease on PSMA PET/CT using multivariable logistic regression for pretreatment patients and multivariable Cox regression for post-RP patients. We also compared select transcriptomic signatures between patients with localized and nonlocalized diseases. Five hundred eighty-six patients were included (pretreatment: n = 329; post-RP: n = 257). Higher Decipher scores were associated with nonlocalized disease on PSMA PET/CT both pretreatment (odds ratio, 1.18 [95% CI, 1.03 to 1.36] per 0.1 increase in Decipher score, P = .02) and post-RP (hazard ratio, 1.15 [95% CI, 1.05 to 1.27] per 0.1 increase in Decipher score, P = .003). In the pretreatment setting, nonlocalized disease was associated with higher rates of TP53 mutations and lower rates of PAM50 luminal A subtype compared with localized disease. In the post-RP setting, overexpression of signatures related to metabolism, DNA repair, and androgen receptor signaling were associated with higher rates of nonlocalized disease. Higher Decipher scores were associated with nonlocalized disease identified on PSMA PET/CT both pretreatment and post-RP. There were several transcriptomic differences between localized and nonlocalized diseases in both settings.

THADA-IGF2BP3 gene fusions in thyroid fine needle aspiration is involved in the pathway to "noninvasive follicular thyroid neoplasm with papillary-like nuclear features".

The increased usage and adaptation of molecular testing of thyroid fine needle aspirations (FNA) has expanded the variety and number of gene fusions identified. While the identified number of molecular alterations is increasing, the definitive association between preoperative molecular analysis and phenotype has yet to be established. The aim of this study was to examine Thyroid adenoma-associated (THADA)-IGF2BP3 molecular fusions with FNA categorization, surgical pathology diagnosis, and other molecular alterations detected by ThyroSeq Genomic Classifier testing. FNA cytology samples of thyroid nodules from 04/2017 to 01/2023 with the diagnosis of atypia of undetermined significance or follicular lesion of undetermined significance (AUS/FLUS; Bethesda III) or follicular neoplasm suspicious for follicular neoplasm (FN/SFN; Bethesda IV) with associated ThyroSeqV3 testing were reviewed. Parameters including patient demographics, FNA diagnosis, ThyroSeq V3 results, and surgical pathology follow up were examined. 87 out of 249 (35%) FNA specimens of thyroid nodules displayed molecular alterations. 64 cases (74%) had a cytology diagnosis of AUS and 23 (26%) had FN. RAS mutation was observed in 48 cases. On surgical follow-up, 17 (35%) cases showed non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP), while 14 (29%) patients had a malignant diagnosis. THADA-IGF2BP3 fusions were seen in 8 cases, all with NIFTP on surgical pathology follow-up (100%). Analysis of THADA-IGF2BP3 fusion, in our institutional series, shows close association with NIFTP cases. THADA-IGF2BP3 fusion, which seems to be a favorable prognostic indicator in general, may serve as a molecular marker for non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP).

Development of a Longitudinal Prostate Cancer Transcriptomic and Clinical Data Linkage

Although tissue-based gene expression testing has become widely used for prostate cancer risk stratification, its prognostic performance in the setting of clinical care is not well understood. To develop a linkage between a prostate genomic classifier (GC) and clinical data across payers and sites of care in the US. In this cohort study, clinical and transcriptomic data from clinical use of a prostate GC between 2016 and 2022 were linked with data aggregated from insurance claims, pharmacy records, and electronic health record (EHR) data. Participants were anonymously linked between datasets by deterministic methods through a deidentification engine using encrypted tokens. Algorithms were developed and refined for identifying prostate cancer diagnoses, treatment timing, and clinical outcomes using diagnosis codes, Common Procedural Terminology codes, pharmacy codes, Systematized Medical Nomenclature for Medicine clinical terms, and unstructured text in the EHR. Data analysis was performed from January 2023 to January 2024. Diagnosis of prostate cancer. The primary outcomes were biochemical recurrence and development of prostate cancer metastases after diagnosis or radical prostatectomy (RP). The sensitivity of the linkage and identification algorithms for clinical and administrative data were calculated relative to clinical and pathological information obtained during the GC testing process as the reference standard. A total of 92 976 of 95 578 (97.2%) participants who underwent prostate GC testing were successfully linked to administrative and clinical data, including 53 871 who underwent biopsy testing and 39 105 who underwent RP testing. The median (IQR) age at GC testing was 66.4 (61.0-71.0) years. The sensitivity of the EHR linkage data for prostate cancer diagnoses was 85.0% (95% CI, 84.7%-85.2%), including 80.8% (95% CI, 80.4%-81.1%) for biopsy-tested participants and 90.8% (95% CI, 90.5%-91.0%) for RP-tested participants. Year of treatment was concordant in 97.9% (95% CI, 97.7%-98.1%) of those undergoing GC testing at RP, and 86.0% (95% CI, 85.6%-86.4%) among participants undergoing biopsy testing. The sensitivity of the linkage was 48.6% (95% CI, 48.1%-49.1%) for identifying RP and 50.1% (95% CI, 49.7%-50.5%) for identifying prostate biopsy. This study established a national-scale linkage of transcriptomic and longitudinal clinical data yielding high accuracy for identifying key clinical junctures, including diagnosis, treatment, and early cancer outcome. This resource can be leveraged to enhance understandings of disease biology, patterns of care, and treatment effectiveness.

Abstract PO2-19-02: NRG-BR009: Phase III Trial Evaluating Addition of Adjuvant Chemotherapy to Ovarian Function Suppression + Endocrine Therapy in Premenopausal Women with pN0-1, HR+/HER2- Breast Cancer and Oncotype Recurrence Score ≤25 (OFSET)

Abstract Background: Identifying pts with HR-positive/HER2-negative breast cancer (BC) who benefit from adjuvant chemotherapy (ACT) has been a major research focus over the past 20 years. Development and clinical application of genomic classifiers such as the 21-gene recurrence score (RS) has contributed to the biologic understanding of BC and has refined pt selection for ACT. The TAILORx and RxPONDER clinical trials demonstrated that RS identifies many postmenopausal pts with node-negative and node-positive BC and RS < 25, who do not benefit from the addition of ACT to endocrine therapy (ET). However, both trials also showed that certain subsets of premenopausal pts (node-negative/high clinical risk/RS 16-20, node-negative/RS 21-25, and node-positive/RS < 25) benefited from the addition of ACT to ET. Most premenopausal pts in these two trials did not receive ovarian function suppression (OFS) as part of their ET regimen. Given the observed benefit from OFS in high-risk premenopausal pts with HR-positive/HER2-negative BC in the SOFT and TEXT trials, many questioned whether all or part of the observed ACT benefit in the TAILORx/RxPONDER trials may have been the result of chemotherapy-induced OFS. To address this question, OFSET is a Phase III, multicenter clinical trial evaluating the addition of ACT to OFS+ET vs. OFS+ET alone. Methods: We hypothesize that the addition of ACT to OFS+ET is superior to OFS+ET in improving invasive breast cancer-free survival (IBCFS) among premenopausal, early-stage BC pts with HR-positive/HER2-negative tumors, and a 21-gene RS between 16-25 (for pN0 pts) and 0-25 (for pN1 pts). Secondary objectives include invasive disease-free survival (IDFS), overall survival (OS), distant recurrence-free interval (DRFI), breast cancer-free interval (BCFI), and health-related quality of life (HRQOL). Eligible pts must be node-negative with RS 16-20 (plus high clinical risk), or RS 21-25, or have 1-3 positive nodes with RS < 25. Stratification is by nodal status/RS status (pN0 RS 16-25 vs pN1 RS 0-15 and pN1 RS 16-25), intent to receive CDK4/6 inhibitor (yes; no), and age (18-39 vs ≥40). Pts are randomized after surgery to either OFS+ET or ACT followed by OFS+ET. ET is an aromatase inhibitor per investigator discretion, but tamoxifen is allowed if pts do not tolerate the AI or if OFS is incomplete. Radiation therapy will be administered per investigator discretion according to protocol guidelines. The HRQOL sub-study will assess differences in severe menopausal symptoms, measured by the FACT ESS-19 score, between the arms, as well as increased pain severity (PROMIS) during ACT+OFS+ET compared to OFS+ET. Blood and tumor specimens will be collected for future research. The accrual of 3,960 pts is anticipated to be completed in seven years and seven mos. Based on data from NSABP B-28 and RxPONDER, the 5-year IBCFS of pN1 pts on the ACT+OFS+ET arm is estimated at 92.3%. Based on data from TAILORx, the 5-year IBCFS of pN0 pts on the ACT arm is ~95%. Assuming 56% of the pts to be pN0 and 44% pN1, a 0.5% annual loss-to-follow-up rate, the definitive analyses to detect a hazard ratio: 0.75 with ACT+OFS+ET vs. OFS+ET, with one-sided alpha of 0.025 and 80% power will require 380 IBCFS events, which are expected to occur ~11 years after study initiation. The OFSET study is expected to be activated in the third quarter of 2023. Current accrual (06-19-2023) is 0/3,960 Support: U10CA180868, U10CA180822, UG1CA189867, U24CA196067. NCT05879926. Citation Format: Eleftherios Mamounas, Gong Tang, Shannon Puhalla, Sandra Swain, Patricia Ganz, N. Lynn Henry, Reena Cecchini, Sonya Reid, Priya Rastogi, Charles Geyer, Julia White, Amy Clark, Tufia Haddad, Gregory Vidal, Norman Wolmark. NRG-BR009: Phase III Trial Evaluating Addition of Adjuvant Chemotherapy to Ovarian Function Suppression + Endocrine Therapy in Premenopausal Women with pN0-1, HR+/HER2- Breast Cancer and Oncotype Recurrence Score ≤25 (OFSET) [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-19-02.

Abstract PO1-19-03: The T-REX trial: a randomized international non-inferiority trial on Tailored Regional EXternal beam radiotherapy in clinically node-negative breast cancer patients with 1-2 sentinel node macrometastases

Abstract Background: Modern systemic treatment has reduced the incidence of regional recurrences and improved survival in breast cancer (BC). It is thus questionable whether regional radiotherapy (RT) is still indicated in patients with sentinel lymph node (SLN) macrometastases. Postoperative regional RT is associated with an increased risk of arm morbidity, pneumonitis, cardiac disease, and secondary cancer. Therefore, there is a need to individualize the indication for regional RT in relation to risk of recurrence. Trial design: In this multicenter, prospective randomized phase 3 trial, eligible patients have a clinically node-negative, estrogen receptor-positive, HER2-negative BC with 1-2 SLN macrometastases, and have not undergone completion axillary lymph node dissection. Participants are randomly assigned to receive regional RT (standard arm) or not (intervention arm). Regional RT includes the axillary levels I-III and the supraclavicular fossa. Internal mammary nodes are targeted in selected patients. After breast-conserving surgery (BCS), RT to the remaining breast is given in both groups while after mastectomy, chest-wall RT is only given in the standard arm. In the intervention arm, chest wall RT may be indicated in selected cases with extensive multifocality, according to national guidelines. RT quality assurance is an integral part of the trial. In addition, material from the primary tumor, SLN metastases and any recurrences is subjected to gene expression analysis to identify both prognostic markers for locoregional recurrence and predictive markers for the benefit of regional RT. After confirmation of eligibility and written informed consent, patients are randomized 1:1 between the treatment arms. Allocation is stratified by trial site and breast surgery (BCS vs. mastectomy). Participation in T-REX should not affect decisions on systemic adjuvant treatment. Eligibility criteria: Trial inclusion and exclusion criteria are given in Table 1. Specific aims: The main aim of the trial is to investigate if the omission of regional RT is non-inferior to routine regional RT in clinically node-negative BC patients with estrogen receptor-positive, HER2-negative T1-2 tumors with 1-2 SLN macrometastases not receiving axillary lymph node dissection. Secondary aims are to investigate whether refraining from regional RT reduces arm morbidity and late RT side effects, and improves short- and long-term health-related quality of life. In addition, the use of genomic classifiers for the prognostication of locoregional recurrences and the prediction of a benefit from regional RT will be investigated. Statistical methods: Primary outcome is recurrence free survival (RFS) at five years. Non-inferiority will be declared if the outcome in the intervention arm is not more than 4.5 percentage units below the standard arm, corresponding to a hazard ratio of 1.41 assuming 88% 5-year RFS with standard treatment. Secondary outcomes include locoregional recurrence, overall survival, patient-reported arm morbidity, and health-related quality of life. Accrual: The trial will include 1350 patients in Sweden, Norway and Finland from April 2023 to December 2028. First sites have been opened in April 2023. Contact information: Primary Investigator: Sara Alkner, Skåne University Hospital, Lund University, sara.alkner@med.lu.se. Responsible for the biobank: Per Karlsson, Sahlgrenska University Hospital, Gothenburg University, per.karlsson@oncology.gu.se. Inclusion and exclusion criteria Citation Format: Sara Alkner, Jana de Boniface, Dan Lundstedt, Ingvil Mjaaland, Lisa Rydén, Johan vikström, Pär-Ola Bendahl, Erik Holmberg, Helena Sackey, Elinore Wieslander, Per Karlsson. The T-REX trial: a randomized international non-inferiority trial on Tailored Regional EXternal beam radiotherapy in clinically node-negative breast cancer patients with 1-2 sentinel node macrometastases [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-19-03.

Idiopathic Pulmonary Fibrosis: From Common Microscopy to Single-Cell Biology and Precision Medicine.

Idiopathic pulmonary fibrosis is a chronic, progressive, and usually fatal lung disease of unknown etiology and is included in the large, complex, and heterogeneous group of interstitial lung diseases (ILD). IPF is characterized by an aberrant activation of epithelial cells and fibroblasts and excessive accumulation of extracellular matrix, resulting in the progressive destruction of the lung architecture. Here we approach the fascinating historical evolution of our knowledge about this disorder from the past century, when most efforts were focused on ILD classification and terminology, until the current century, when the explosive progress in molecular genetics, epigenetics, and multiomics, as well as the development of complex computational tools, resulted in a huge advance in unveiling the pathogenic mechanisms of the disease. Recent advances in artificial intelligence, machine and deep learning, and artificial neural networks show promising results in identifying lung fibrotic patterns in high-resolution computed tomography or helping to create a tissue genomic classifier for specific diagnosis. Finally, incipient approaches to precision medicine are ongoing in the area of pharmacogenetics.

M6ACali: machine learning-powered calibration for accurate m6A detection in MeRIP-Seq.

We present m6ACali, a novel machine-learning framework aimed at enhancing the accuracy of N6-methyladenosine (m6A) epitranscriptome profiling by reducing the impact of non-specific antibody enrichment in MeRIP-Seq. The calibration model serves as a genomic feature-based classifier that refines the identification of m6A sites, distinguishing those genuinely present from those that can be detected in in-vitro transcribed (IVT) control experiments. We find that m6ACali effectively identifies non-specific binding peaks reported by exomePeak2 and MACS2 in novel MeRIP-Seq datasets without the need for paired IVT controls. The model interpretation revealed that off-target antibody binding sites commonly occur at short exons and short mRNAs, originating from high read coverage regions that share the motif sequence with true m6A sites. We also reveal that the ML strategy can efficiently adjust differentially methylated peaks and other antibody-dependent, base-resolution m6A detection techniques. As a result, m6ACali offers a promising method for the universal enhancement of m6A profiles generated by MeRIP-Seq experiments, elevating the benchmark for omics-level m6A data integration.

386 The Analysis of N-glycans and Collagen to Predict Prostate Adenocarcinoma Outcome

OBJECTIVES/GOALS: Distinguishing indolent from aggressive prostate cancer and early identification of men at risk of developing aggressive, metastatic disease is of great importance. We aim to explore the relationship between N-glycan and collagen composition in prostate tumor tissue and the long-term outcome of the disease. METHODS/STUDY POPULATION: Matrix assisted laser desorption/ionization mass spectrometry can be utilized to characterize N-glycan profiles in formalin fixed paraffin embedded tissues. Collagen may also be characterized using ECM-targeted collagenase MALDI imaging. These approaches were used to analyze prostatectomy samples with different clinical outcomes. Tissue microarrays containing tissues from 75 non-progressors (no evidence of disease; NED) and 50 metastatic cases (MET) were examined. From a combined list of 90 N-glycans and 500 collagenase peptides, the average AUC intensity value for each glycan and collagen peptide was extracted and assessed as a predictor of metastatic progression. Ancestral informative markers were analyzed and polygenic hazard risk scores were generated for samples as well. RESULTS/ANTICIPATED RESULTS: Three N-glycans and three collagen peptides were found to discriminate between NED and MET cases with statistical significance. The best performing N-glycan was Hex6HexNAc6Fuc1 with an AUC of 0.77 (p<0.001). While the best performing collagen peptide was COL1A2 with an AUC of C 0.77 (p<0.001). DISCUSSION/SIGNIFICANCE: Both a collagen peptide and N-glycan were discovered as promising biomarkers to predict metastasis. Future validation studies are needed to confirm biomarker potential and to determine if the addition of these biomarkers can strengthen current genomic classifier’s ability to predict metastatic prostate cancer.

Quantification and molecular correlates of tertiary lymphoid structures in primary prostate cancer.

To morphologically describe tertiary lymphoid structures (TLS) in prostatectomy specimens and correlate them with clinical and transcriptomic features. A total of 72 consecutive cases of entirely submitted radical prostatectomy (RP) patients tested with the Decipher Genomic Classifier were included in the study. Images were manually annotated using QuPath tools to denote tumor regions and each cluster of TLS. Clusters of lymphocytes that were surrounded on all four sides by tumor were defined as intra-tumor TLS (IT-TLS). Clusters of lymphocytes at the leading edge of carcinoma with either the prostatic pseudocapsule or benign parenchyma at one end were defined as peri-tumor TLS (PT-TLS). A classification algorithm to distinguish lymphocytes from non-lymphocytic cells using a supervised machine learning model was used. The associations between TLS formation and 265 gene expression-based signatures were examined. The magnitude of total TLS correlations with primary tumor gene expression signatures was moderate (~0.35-0.5) with several HLA, T-cell and B-cell Cluster signatures, showing positive correlation with various metrics for quantification of TLS. On the other hand, immune suppressive signatures (Treg, MDSC) were negatively correlated. While signatures for macrophages, NK cells and other immune cell types were uncorrelated for the most part. PT-TLS was associated with MHC signatures while IT TLS correlated with MHC andT-cell signatures. Clusters of inflammatory cells in the RP specimen can be divided spatially into PT TLS and IT-TLS, each with its unique molecular correlates of tumor immune microenvironment. The presence of TLS is positively correlated with MHC signatures, T- cell and B-cell cluster signatures but, negatively correlated with immune suppressive signatures. A subset of prostate cancer demonstrate a robust inflammatory response, and warrant further characterization in larger cohorts.

Abstract 7669: Use of computational pathology to predict biochemical recurrence in prostate cancer (Pca) (Rp) patients following radical prostatectomy: Evaluation in low decipher risk category

Abstract Background: Current tools for predicting prostate cancer biochemical recurrence (BCR) after RP often depend on parameters determined by pathologists, such as tumor grade, which is known to vary between reviewers. Genomic risk classifiers provide useful information but require substantial tissue, are costly, and are not commonly accessible in many medical centers. The study presents an artificial intelligence (AI) model for automated risk assessment of biochemical recurrence (BCR) by analyzing nuclear morphologic patterns from Pca archival H&E slides. Nuclear morphometric features are essential for disease diagnosis and gaining insights into cellular functions. Specifically, we sought to evaluate whether the computational pathology approach could provide additional granular risk stratification within the low-risk group identified by Decipher. Methods: The study employed two cohorts from the University of Pennsylvania D1 and D2. D1 comprised 180 patients, while D2 comprised 175 patients, including 63 individuals from the Decipher low-risk group. None of the patients in either cohort had received any pre-operative treatments. Within the Decipher cohort, a tumor segmentation model was created using the U-net deep learning network. The HoVer-Net model was used to both segment and classify nuclei. The feature extracted included a combination of nuclear texture and quantitative measurements of the spatial arrangement of nuclei. The eleven most significant features, selected via the least absolute shrinkage and selection operator (LASSO), were utilized to build a Cox regression model for predicting the risk of BCR in D1. In D2, patients were classified as either low-risk or high-risk for BCR based on the median risk score derived from D1. Results: Patients from D1 identified as high risk by the AI model experienced shorter survival, with a median BCR time of 27 months, in contrast to 55 months for those classified as low risk. The AI model demonstrated significant prognostic value for BCR in both D1 (HR = 6.82, 95% confidence interval [CI]: 3.54-13.12, p < 0.0019), and D2 (HR = 2.72, 95% CI: 1.53-4.82, p < 0.0032). Furthermore, the model effectively stratified the Decipher low-risk group in D2 into distinct low and high-risk categories (HR = 4.52, 95% confidence interval [CI]: 1.70-12.05, p < 0.0085). The most prognostic features identified included five related to nuclei shape diversity (Minor Axis Length, Eccentricity, Equivalent Diameter, Solidity, and Circularity) in conjunction with nine nuclear texture features. Conclusions: The AI model's findings suggest that a digital image-based prognostic classifier for prostate cancer could serve as an alternative or complementary method to molecular-based companion risk tests. Additional, independent multi-site and prospective validation of these findings are warranted. Citation Format: Kamal Hammouda, Tilak Pathak, Tuomas Mirtti, Priti Lal, Shilpa Gupta, Anant Madabhushi. Use of computational pathology to predict biochemical recurrence in prostate cancer (Pca) (Rp) patients following radical prostatectomy: Evaluation in low decipher risk category [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 7669.

Treatment intensification strategies for men undergoing definitive radiotherapy for high-risk prostate cancer.

Treatment intensification of external beam radiotherapy (EBRT) plays a crucial role in the treatment of high-risk prostate cancer. We performed a critical narrative review of the relevant literature and present new developments in evidence-based treatment intensification strategies. For men with high-risk prostate cancer, there is strong evidence to support prolonging androgen deprivation therapy (ADT) to 18-36months and escalating the dose to the prostate using a brachytherapy boost. A potentially less toxic alternative to a brachytherapy boost is delivering a focal boost to dominant intraprostatic lesions using EBRT. In patients who meet STAMPEDE high-risk criteria, there is evidence to support adding a second-generation anti-androgen agent, such as abiraterone acetate, to long-term ADT. Elective pelvic lymph node irradiation may be beneficial in select patients, though more prospective data is needed to elucidate the group of patients who may benefit the most. Tumor genomic classifier (GC) testing and advanced molecular imaging will likely play a role in improving patient selection for treatment intensification as well as contribute to the evolution of treatment intensification strategies for future patients. Treatment intensification using a combination of EBRT, advanced hormonal therapies, and brachytherapy may improve patient outcomes and survival in men with high-risk prostate cancer. Shared decision-making between patients and multidisciplinary teams of radiation oncologists, urologists, and medical oncologists is essential for personalizing care in this setting and deciding which strategies make sense for individual patients.