RNA sequencing is becoming increasingly common in precision oncology, in both clinical and research settings, for transcriptome profiling, gene-fusion detection, and biomarker discovery. RNA-sequencing analysis of specimens obtained via minimally invasive procedures such as small biopsy, fine needle aspiration, and exfoliation offers a powerful method for analyzing gene expression patterns and detecting RNA-level changes associated with cancers that are either difficult to collect or require longitudinal sampling. However, pre-analytical factors (e.g., details of specimen collection, processing, and storage workflow) influence not only RNA-sequencing success rates but also the quality and accuracy of sequencing results, which may affect patient care and research progress. Minimally invasive specimens are associated with a unique set of pre-analytical challenges owing to their small size, limited RNA yield, and distinct workflows. To address the need for evidence-based guidance, this review by a working group of National Cancer Institute grantees and intramural and extramural researchers identifies pre-analytical best practices for minimally invasive specimens destined for RNA-sequencing analysis, based on the available literature and their collective experience. Strategies for assessing specimen adequacy and RNA quality, maximizing tumor content, and minimizing specimen loss and RNA degradation due to pre-analytical handling are specified for small tissue and cytology specimens. By integrating current evidence and institutional insights, this review provides a practical framework for enhancing RNA-sequencing reliability and reproducibility in both clinical and research workflows. RNA, or ribonucleic acid, carries the instructions that cells use to function and grow. RNA sequencing is a laboratory method that allows scientists to see which genes are active or altered. In cancer, this information helps explain how tumors behave, change over time, and respond to treatment, and it can support diagnosis and treatment planning. RNA sequencing is especially valuable when only small samples are available, such as needle biopsies, fine-needle aspirations, or cells released into body fluids. These minimally invasive samples are often the only practical option when tumors are difficult to reach or when repeat testing is needed. However, working with small samples is challenging because the amount of RNA is limited and easily damaged. Problems during collection, storage, or processing can reduce RNA quality and lead to unreliable results. To address these challenges, experts supported by the National Cancer Institute reviewed both published studies and real-world laboratory experience to develop practical guidance on how to collect, handle, and preserve small samples for RNA sequencing. Following these best practices improves the reliability of testing and helps ensure that meaningful information can be obtained even from very limited material.

Endometrial carcinoma (EC) is a common gynecological cancer with rising incidence driven by obesity and aging populations. Accurate and timely molecular classification is critical for guiding personalized oncology treatment, especially in early-stage high-grade endometrioid carcinoma. Here we present a large scale, retrospective multicenter validation of a novel POLE-POLD1 mutation assay for use in molecular characterization of EC. We evaluated the analytical performance and robustness of the novel Idylla™ POLE-POLD1 Mutation Assay, a cartridge-based PCR platform optimized for FFPE tissue. Performance comparators were established NGS reference methods. Overall, 544 formalin-fixed, paraffin embedded (FFPE) EC cases from diagnostic pathology of ten centers in Europe and North America were included. Of 544 samples, 520 revealed POLE-POLD1 test and comparator results, yielding an overall concordance of 97

PURPOSE Mutations in TP53 , detected in over 20% of diffuse large B-cell lymphomas (DLBCLs), are associated with poor prognosis. However, clinical outcomes among patients with TP53 -mutant disease vary, with some patients showing treatment responses similar to those with wild-type TP53 . This study aims to understand the clinical and molecular determinants underlying poor outcomes in TP53 -mutant DLBCL. METHODS Clinical and molecular data for 3,091 patients were derived from 10 cohorts of patients with newly diagnosed DLBCL treated with frontline rituximab-based immunochemotherapy regimens. Targeted or whole-exome/whole-genome sequencing was available for all patients. Bulk RNA-seq was analyzed for 591 patient samples. The primary outcome measures were progression-free survival (PFS) and overall survival (OS). RESULTS TP53- mutant DLBCL differed from wild-type disease in pattern and number of genetic lesions, malignant B-cell expression states, and tumor microenvironment composition. TP53 mutations were 6-fold more prevalent than MYC/BCL2/BCL6 double-/triple-hit status, but conferred similar adverse prognostic risk. Among patients with TP53 -mutant disease, variant allele frequency (VAF) further stratified risk, with patients featuring VAF ≥ 75% (indicative of loss of heterozygosity) experiencing significantly inferior PFS/OS. Downregulation of interferon signaling and lower macrophage content were identified in TP53 -mutant samples derived from patients with poor outcomes or VAF ≥ 75%. TP53 mutations were adversely prognostic among patients with DLBCL assigned to specific LymphGen subtypes (EZB, MCD), malignant B-cell states (S1), and ecotypes (LE4, LE7, LE8), whereas outcomes were similar to wild-type disease within other molecular subtypes. In re-examination of the Phoenix trial data, addition of ibrutinib to R-CHOP improved PFS in patients with TP53 -mutant DLBCL and abrogated the deleterious impact of high VAF, irrespective of patients' age. CONCLUSION The poor prognosis of TP53 -mutant DLBCL is dependent on intrinsic features, such as VAF, and modulated by co-occurring genomic lesions or lymphoma cell-intrinsic or microenvironmental expression patterns.

Histiocytoses are clonal hematopoietic disorders frequently driven by mutations mapping to the BRAF and MEK1 and MEK2 kinases. Currently, however, the developmental origins of histiocytoses in patients are not well understood, and clinically meaningful therapeutic targets outside of BRAF and MEK are undefined. In this study, we uncovered activating mutations in CSF1R and rearrangements in RET and ALK that conferred dramatic responses to selective inhibition of RET (selpercatinib) and crizotinib, respectively, in patients with histiocytosis.

Background: Molecular classifications of diffuse large B-cell lymphoma (DLBCL) can identify patient groups that benefit from distinct, innovative therapies. However, their implementation in routine practice has yet to be demonstrated. DLBclass (Chapuy, 2025) is a probabilistic, neural network–based classifier that assigns DLBCL cases to one of five genetic clusters (C1–C5). MSK-IMPACT Heme is a clinical NGS panel for detecting somatic mutations and allele-specific copy number alterations (CNAs) (Ptashkin, 2023). Here, we demonstrate how MSK-IMPACT Heme data collected during routine clinical care across various disease states enable the classification of cases into DLBclass clusters. Methods: DLBCL samples underwent MSK-IMPACT Heme sequencing along with clinical evaluation. This enabled the generation of DLBclass inputs: CNAs were called with FACETS, mutations annotated per Ptashkin (2023), structural variants identified by FISH, and cell-of-origin classified using the Hans algorithm. Technical validation: A total of 531 unique samples were initially assessed: 139 were excluded for low tumor purity (<20%) or failed FACETS quality control, resulting in a final cohort of 392 samples. This included 279 de novo DLBCL cases (184 pre- & 95 post-treatment) and 113 transformed indolent NHL (tiNHL) cases. Gene coverage of DLBclass cluster assignments ranged from 52% to 98% across the MSK-IMPACT Heme panels. Among the pre-treatment de novo DLBCL samples, cases were distributed across clusters as follows: 11% in C1, 28% in C2, 31% in C3, 12% in C4, and 17% in C5. Cluster C3 was significantly enriched compared to the published reference DLBclass datasets (p < 0.001), while the distribution of the other clusters mirrored that of the reference cohort. Using a 0.7 confidence threshold, we observed a lower proportion of high-confidence predictions in clusters C1, C4, and C5 relative to the DLBclass data. Across 45 matched samples with both WES and MSK-IMPACT Heme sequencing, cluster assignments were consistent in 71% of cases. Among the 13 mismatches, 12 involved cluster C2, highlighting variability in CNA-driven clusters between platforms. Given that C2 is primarily defined by CNAs, we investigated the impact of CNA removal on cluster assignment. Excluding CNAs led to a reduction in C2-classified samples, from 33% to 3.6%. Notably, in post-treatment samples, C2 had comprised 42%, underscoring its relevance in that clinical context. Upon CNA removal, many C2 samples shifted toward C3, suggesting that in the absence of CNAs, mutation profiles and panel breadth play a dominant role in cluster classification. Applying the DLBclass framework to routine MSK-IMPACT Heme data reproduced cluster patterns seen in reference datasets, validating its use in clinical samples and supporting further study of cluster biology and phenotypes. Biological and clinical correlations: In the de novo DLBCL cohort, the C3 cluster was significantly enriched for germinal center B-cell (GCB)–type cases, while C5 was more frequent among non-GCB cases (p < 0.001), both consistent with Chapuy (2025). Additionally, C3 and C5 showed enrichment for double/triple-hit lymphomas and primary CNS lymphomas (PCNSL), respectively. Cluster C2 was associated with low tumor mutational burden (TMB), whereas C4 correlated with high TMB. Patterns of progression-free survival mirrored those reported in the original DLBclass cohort, suggesting consistent clinical behavior across datasets. Among 15 patients with sequential samples, 80% retained stable cluster assignments over time. Changes in cluster confidence were mostly observed within C2, indicating overall low genomic heterogeneity across serial samples. Applying the DLBclass classifier to samples obtained after histologic transformation, we found that C3 was enriched in patients with prior follicular lymphoma, C2 in those with transformed chronic lymphocytic leukemia and marginal zone lymphoma (p < 0.001). MZL samples also showed enrichment in C5 (p < 0.003). Conclusion: Our findings are the first to demonstrate the feasibility and utility of applying the DLBclass genomic classifier to routine clinical samples using the MSK-IMPACT Heme assay. In our cohort, the classifier reproduced cluster distributions similar to reference datasets, establishing a basis for incorporating genomic subtyping into clinical workflows and improving molecular classification to guide personalized therapeutic strategies in DLBCL.

Malignant T-cell transformation after chimeric antigen receptor (CAR) T-cell therapy has been described, but the contribution of CAR integration to oncogenesis is not clear. Here we report a case of a T-cell lymphoma harboring a lentiviral integration in a known tumor suppressor, TP53, which developed in a patient with multiple myeloma after B-cell maturation antigen (BCMA) CAR T-cell therapy.

PURPOSE MAP2K1/MEK1 mutations are potentially actionable drivers in cancer. MAP2K1 mutations have been functionally classified into three groups according to their dependency on upstream RAS/RAF signaling. However, the clinical efficacy of mitogen-activated protein kinase (MAPK) pathway inhibitors (MAPKi) for MAP2K1-mutant tumors is not well defined. We sought to characterize the genomic and clinical landscape of MAP2K1 mutant tumors to evaluate the relationship between MAP2K1 mutation class and clinical activity of MAPKi. METHODS We interrogated American Association for Cancer Research (AACR) GENIE (v13) to analyze solid tumors with MAP2K1 mutations. We performed a systematic review and meta-analysis of published reports of patients with MAP2K1-mutant cancers treated with MAPKi according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The primary end point was progression-free survival (PFS), and secondary end points were overall treatment response rate (ORR), duration of response (DOR), and overall survival. RESULTS In the AACR GENIE data set, class 2 MAP2K1 mutations (63%) were more prevalent than class 1 (24%) and class 3 (13%) mutations ( P < .0001). Co-occurring MAPK pathway-activating mutations were more likely to occur in class 1 versus class 2 or 3 MAP2K1-mutant tumors ( P < .0001). Our systematic meta-analysis of the literature identified 46 patients with MAP2K1-mutant tumors who received MAPKi. In these patients, ORR was 28% and median PFS was 3.9 months. ORR did not differ according to MAP2K1 mutation class or cancer type. However, patients with class 2 mutations experienced longer PFS (5.0 months) and DOR (23.8 months) compared with patients with class 1, 3, or unclassified MAP2K1 mutations (PFS 3.5 months, P = .04; DOR 4.2 months, P = .02). CONCLUSION Patients with class 2 MAP2K1 mutations represent a novel subgroup that may derive benefit from MAPKi. Prospective clinical studies with novel MAPKi regimens are warranted in these patients.

Tumor mutational burden (TMB) has emerged as a potential surrogate for neoantigen load and an indicator of immune checkpoint (IC)-blockade response; however, its precise significance in breast cancer (BC) is not fully understood. Here, we comprehensively characterized the genomic repertoire of BCs with a TMB ≥ 10 mut/Mb (TMB-high [n = 527]) to identify putative predictors of importance. The predominant mutational signature was apolipoprotein B mRNA-editing enzyme catalytic polypeptide (APOBEC) in 64.7% of tumors. TMB-high BCs were enriched in KMT2C, ARID1A, PTEN, NF1, and RB1 alterations, which are associated with APOBEC mutagenesis. Further identified were loss-of-function ARID1A and PTEN alterations, which are linked to immune cell exclusion. ESR1 p.E380Q prevailed among all ESR1 hotspot mutations, supporting APOBEC-mediated effects. Finally, mutations in DNA damage response and repair genes were seen at a higher frequency than in non-TMB-high BCs. These findings provide justification for exploring combined pharmacologic inhibition to improve IC-based efficacy.

Table S2. Oncogenic/Likely-oncogenic structural variants in GBC

Most patients diagnosed with mantle cell lymphoma (MCL) experience extended remissions following frontline chemoimmunotherapy, yet with with extended follow-up, relapses seem nearly inevitable. This study aimed to define the genomic landscape of MCL at diagnosis and relapse and investigate the clonal evolutionary dynamics associated with progression of disease (POD). We conducted comprehensive genomic sequencing on 214 tumor specimens from 189 patients, including 144 treatment-naïve and 70 POD samples, with 25 patients providing longitudinal paired samples pre-treatment and at POD. Comparative analyses were performed on single nucleotide variants (SNVs), insertions/deletions (indels), and copy number alterations (CNAs) to assess genomic differences between treatment-naïve and relapsed specimens. Additionally, mutational signatures were evaluated in pre-treatment samples, stratified by time to progression (≤24 months vs. >24 months). One hundred patients who received standard frontline chemoimmunotherapy were included in the survival analysis. Genomic profiles of pre-treatment specimens from patients who ultimately relapsed were strikingly similar to those observed in POD, while distinctly different from profiles associated with prolonged remissions. This genomic 'stability' was further confirmed by analysis of 25 paired specimens, demonstrating a remarkable genomic concordance despite extended remission periods (median >3 years), without a clear pattern of acquired alterations Our findings suggest that MCL relapse is predominantly driven by pre-existing malignant clones at diagnosis, rather than by new evolutionary events, underscoring the importance of early detection and eradication of resistant clones to improve long-term outcomes.

BACKGROUND AND OBJECTIVE:Divergent differentiation and histologic subtypes are common findings in urothelial carcinoma (UC). Clinically relevant genomic alterations and oncogenic drivers of individual subtypes remain poorly defined. We characterized surgical outcomes and the genomic landscape of UC with aberrant histology (UCAH), with a focus on biomarkers and targetable alterations. METHODS:The clinical cohort comprised 3052 patients who underwent radical cystectomy (RC) with or without neoadjuvant chemotherapy. Targeted exon sequencing was performed for a genomic cohort of 1060 bladder tumors from RC or transurethral resection specimens. We characterized the frequency of oncogenic mutations and targetable alterations, and the tumor mutational burden (TMB) of each subtype. We defined the clonal relatedness of morphologically distinct regions of tumors with mixed histology. KEY FINDINGS AND LIMITATIONS:Patients with plasmacytoid, micropapillary, sarcomatoid, or mixed-histology tumors had worse cancer-specific survival than patients with pure urothelial histology. ERBB2, FGFR3, and PTEN alterations were most frequent in micropapillary, nested/squamous, and sarcomatoid UC, respectively. TMB was highest in plasmacytoid, neuroendocrine, and micropapillary tumors. Regions of mixed histology had shared clonal origins, but exceptions were observed. The retrospective design and potential for selection bias are limitations of our study. CONCLUSIONS AND CLINICAL IMPLICATIONS:UCAH tumors have distinct patterns of genomic alterations, which may be targetable via novel therapies and have implications for clinical trial inclusion. Biomarker-driven systemic therapy should be explored in patients with histologic subtypes that are associated with worse clinical outcomes.

Background and objective: The source of tissue for genomic profiling of metastatic castration-resistant prostate cancer (mCRPC) is often limited to osseous metastases. To guide patient management, metastatic site selection and the technique for targeted bone biopsies are critical for identifying deleterious gene mutations. Our objective was to identify key parameters associated with successful large-panel DNA sequencing. Methods: We analyzed parameters for 243 men with progressing mCRPC who underwent 269 bone biopsies for genomic profiling between 2014 and 2018. Univariate and multivariate analyses were performed for clinical, imaging (bone scan; fluorodeoxyglucose [FDG] positron emission tomography [PET]; computed tomography [CT]; magnetic resonance imaging), and technical (biopsy site, number of samples, needle gauge) features associated with successful genomic profiling. Key findings and limitations: Overall, 159 of 269 biopsies (59%) generated sufficient tumor material for a genomic profile. Seventy (26%) of the failures were histopathologically negative for mCRPC and 40 (15%) had insufficient tumor for genomic profiling. Of 199 mCRPC samples submitted for molecular testing, 159 (80%) yielded a genomic profile. On univariate analysis, PSA, serum acid phosphatase, number of biopsy samples, FDG PET positivity, CT attenuation, and CT morphology were significantly associated with genomic profiling success. On multivariate analysis, higher FDG maximum standardized uptake value (odds ratio [OR] 7.51, 95% confidence interval [CI] 3.01-18.78; p < 0.001), higher number of biopsy samples (OR 4.73, 95% CI 1.49-15.02; p = 0.008), and lower mean CT attenuation (OR 0.4, 95% CI 0.18-0.89; p = 0.025) were significantly associated with sequencing success. Conclusions and clinical implications: In patients with mCRPC, bone biopsies from sites with metabolic activity and lower CT attenuation are associated with higher success rates for genomic profiling via a large-panel DNA sequencing platform. Patient summary: We identified factors associated with successful genetic testing of bone tissue for patients with metastatic prostate cancer. Our findings may help in guiding the right scan technique and biopsy site for personalized treatment planning. Published by Elsevier B.V. on behalf of European Association of Urology.

Mixed phenotype (MP) in acute leukemias poses unique classification and management dilemmas and can be seen in entities other than de novo mixed phenotype acute leukemia (MPAL). Although WHO classification empirically recommends excluding AML with myelodysplasia related changes (AML-MRC) and therapy related AML (t-AML) with mixed phenotype (referred to as "AML-MP") from MPAL, there is lack of studies investigating the clinical, genetic, and biologic features of AML-MP. We report the first cohort of AML-MP integrating their clinical, immunophenotypic, genomic and transcriptomic features with comparison to MPAL and AML without MP. Patients with AML-MP share similar clinical and genetic features to its AML counterpart but differs from MPAL. AML-MP harbors more frequent RUNX1 mutations than AML without MP and MPAL. RUNX1 mutations or complex karyotypes did not impact the survival of MPAL patients. Unsupervised hierarchal clustering based on immunophenotype identified biologically distinct clusters with phenotype/genotype correlation and outcome differences. Furthermore, transcriptomic analysis showed an enrichment for stemness signature in AML-MP and AML without MP as compared to MPAL. Lastly, MPAL but not AML-MP often switched to lymphoid only immunophenotype after treatment. Expression of transcription factors critical for lymphoid differentiation were upregulated only in MPAL, but not in AML-MP. Our study for the first time demonstrates that AML- MP clinically and biologically resembles its AML counterpart without MP and differs from MPAL, supporting the recommendation to exclude these patients from the diagnosis of MPAL. Future studies are needed to elucidate the molecular mechanism of mixed phenotype in AML. Key points:AML-MP clinically and biologically differs from MPAL but resembles AML. AML-MP shows RUNX1 mutations, stemness and limited lineage plasticity.

Table S1. Sample list (cBioPortal identifiers, ‘DMP_SAMPLE_ID’). Only the primary tumor (if available) or the earliest collected metastasis are included (n=233)

ABSTRACT:Breast implant-associated anaplastic large cell lymphoma (BIA-ALCL) is a type of T-cell lymphoma arising near textured breast implants. In a Dutch population, a higher prevalence of BRCA1/2 was found in BIA-ALCL. We analyzed the risk of BIA-ALCL occurrence related to BRCA in a large population of women with implants followed after breast cancer (BC) mastectomy. We compared the prevalence of BRCA1/2 between women from a large cohort of patients with BC who did and did not develop BIA-ALCL after reconstruction with textured implants. Hazard ratios (HRs) of developing BIA-ALCL were estimated using Cox regression. We also conducted a case-control study. Of 520 patients with BC tested for BRCA, the age-adjusted rate of developing BIA-ALCL for women with BRCA was 16 times the rate of BIA-ALCL among women without BRCA (95% confidence interval [CI], 3.6-76.1; P < .0003). Carrying bilateral implants (HR, 3.9; 95% CI, 0.4-32.7), chemotherapy (HR, 0.95; 95% CI, 0.2-4.2), and radiotherapy (HR, 0.37; 95% CI, 0.04-3.1) were not associated with BIA-ALCL. We also conducted a case-control study with 13 BIA-ALCL patients matched 1:3 with 39 controls. We used a complete enumeration of Bernoulli probability to rule out a nonassociation of BRCA with BIA-ALCL (P = .0002). In this study, we defined the role of BRCA1/2 mutations as a risk factor in developing BIA-ALCL in patients with BC. These results will help women undergoing breast reconstruction or with textured implants in place.