Biology subjects

Pareja, F.

Publications and source records attributed to Pareja, F..

10 recordsLinked to original sources

bioRxiv2026

Evasion of Hepatic ILC1 Immunosurveillance Drives Breast Cancer Liver Metastasis

Metastasis, the dissemination of cancer cells to distant organs, is an inefficient process1, yet remains the leading cause of cancer-related mortality2. The cellular barriers and evasion mechanisms governing organ-specific susceptibility remain incompletely understood3-5, hindering the development of effective anti-metastatic therapies6. Here, we show that liver-resident type 1 innate lymphoid cells (ILC1s) constitute an essential immunosurveillance barrier against breast cancer liver metastasis that can be bypassed through either cancer cell intrinsic or host-dependent mechanisms. In a multi-organ metastatic breast cancer patient cohort, liver metastasis occurred later and was associated with poorer survival than lung metastasis, with elevated body mass index emerging as a clinical risk factor. This metabolic vulnerability was recapitulated in mice, where a high-fat diet induced hepatosteatosis and selectively enhanced breast cancer colonization of the liver. Mechanistically, liver and lung colonization were restrained by ILC1s and circulating natural killer (NK) cells, respectively. Following cancer cell challenge, NK cells expanded and activated, employing lytic granule pathways and the death receptor DR5 for clearance, whereas activated ILC1s selectively required high DR5 expression on cancer cells, supported by AP-2a (TFAP2A) mediated transcriptional activation, for effective immunosurveillance. Heterozygous copy number deletion at TNFRSF10B (encoding DR5) in human tumours reduced DR5 expression and predisposed to liver metastasis. Hepatosteatosis further compromised this barrier by reducing IL-15 expression in macrophages, thereby depleting hepatic ILC1s effects reversible with glucagon-like peptide-1 (GLP-1) receptor agonists. Thus, hepatic ILC1s form a critical organ-specific barrier to breast cancer metastasis, vulnerable to both cancer cell-intrinsic DR5 downregulation and host metabolic dysfunction.

immunology↗

bioRxiv2026

Microfluidic Tissue Array Platform for Personalized Drug Screening Using Tumor Explants or Biopsies

Despite major improvements in molecular characterization of breast cancer, current biomarkers still fall short in accurate treatment prediction. Interrogating tumor tissue ex-vivo in its native conformation is a direct strategy for guiding treatment of individual patients but presents a challenge. In this study, we developed a microfluidic tissue array (FTA) using small biopsy samples (< 1mm3) mimicking physiological flow for consistent exchange of nutrients and waste, retaining the tumor native stroma. Cell/patient-derived breast cancer xenograft tissues were maintained over 2 weeks in the array and their response to therapeutic agents, doxorubicin or neratinib, were interrogated. Drug response in the uFTA showed >2-fold reduction in tumor cell viability which corroborated tumor size shrinkage in mice bearing the same tumor load. EdU/Ki67 assays indicated selective retention of cells with higher proliferative capacity after drug treatment, underscoring in vivo clinical relevance . We have also developed a valved-FTA to increase throughput and variety of treatment conditions on the same chip. Together, this FTA can be staged as a powerful, low-cost benchtop theranostic tool for personalized cancer therapeutics compatible with FDAs New Approach Methods.

cancer biology↗

bioRxiv2025

Integrated histopathologic modeling of detailed tumor subtypes and actionable biomarkers

Accurate cancer subtyping with accompanying molecular characterization is critical for precision oncology. While machine learning approaches have been applied to both digital pathology and cancer genomics, previous work has been limited in sample size and has typically aggregated granular cancer subtypes into coarse groupings, likely obfuscating informative molecular and prognostic associations and phenotypic variation of more detailed tumor subtypes. Accordingly, we collated 378,123 hematoxylin and eosin (H&E)-stained whole-slide images (WSIs) with matched targeted DNA clinical sequencing results and OncoTree detailed cancer subtypes from a real-world cohort of 71,142 patients. Using this scaled, granular dataset and a cancer subtype knowledge graph, we developed Mosaic: a family of calibrated machine learning models using H&E WSI embeddings to classify tumors and identify molecular phenotypes across 163 detailed subtypes. The cancer subtyping module (Aeon) achieved an area under the receiver operating characteristic curve (AUROC) of 0.992 overall, with 161/163 subtypes reaching an AUROC [≥] 0.90 and improved performance over a state-of-the-art genomics-based classifier. The genomic inference module (Paladin) achieved an AUROC [≥] 0.80 for 167 pairs of detailed subtypes and genomic targets. We further used the learned histopathologic representations to i) identify key associations of the histopathologic embeddings with clinical biomarkers; ii) identify unsupervised sub-clusters of tumors with genomic determinants of tumor phenotype; iii) specify granular diagnoses for cancers of unknown primary, evaluated by genomic associations and expected clinical outcome distributions; iv) annotate functional significance for variants of uncertain significance (VUS); and v) identify cases that mimic the phenotypic effect of known DNA variants on H&E in the absence of detectable DNA alterations. Taken together, this work advances our understanding of phenotypic variation of granular tumor subtypes, their relevance to enhanced diagnostics, and their potential utility in risk stratification with multimodal machine learning in cancer.

cancer biology↗

bioRxiv2025

RNA Transcripts Serve as a Template for Double-Strand Break Repair in Human Cells

Double-strand breaks (DSBs) are toxic lesions that lead to genome instability. While canonical DSB repair pathways typically operate independently of RNA, emerging evidence suggests that RNA:DNA hybrids and transcripts near damaged sites can influence repair outcomes. However, a direct role for transcript RNA as a template during DSB repair in human cells is yet to be established. In this study, we designed fluorescent- and sequencing-based assays, which demonstrated that RNA-containing oligonucleotides and messenger RNA serve as templates to promote DSB repair. We conducted a CRISPR/Cas9-based genetic screen to identify factors that promote RNA-templated DSB repair (RT-DSBR), and of the candidate polymerases, we identified DNA polymerase-zeta (Pol{zeta}) as the potential reverse transcriptase that facilitates RT-DSBR. Furthermore, by analyzing sequencing data from cancer genomes, we identified the presence of whole intron deletions, a unique genomic scar reflective of RT-DSBR activity generated when spliced mRNA serves as the repair template. These findings highlight RT-DSBR as an alternative pathway for repairing DSBs in transcribed genes, with potential mutagenic consequences.

molecular biology↗

bioRxiv2024

eIF4A controls translation of estrogen receptor alpha and is a therapeutic target in advanced breast cancer

The majority of human breast cancers are dependent on hormone-stimulated estrogen receptor alpha (ER) and are sensitive to its inhibition. Treatment resistance arises in most advanced cancers due to genetic alterations that promote ligand independent activation of ER itself or ER target genes. Whereas re-targeting of the ER ligand binding domain (LBD) with newer ER antagonists can work in some cases, these drugs are largely ineffective in many genetic backgrounds including ER fusions that lose the LBD or in cancers that hyperactivate ER targets. By identifying the mechanism of ER translation, we herein present an alternative strategy to target ER and difficult to treat ER variants. We find that ER translation is cap-independent and mTOR inhibitor insensitive, but dependent on 5 UTR elements and sensitive to pharmacologic inhibition of the translation initiation factor eIF4A, an mRNA helicase. EIF4A inhibition rapidly reduces expression of ER and short-lived targets of ER such as cyclin D1 and other components of the cyclin D-CDK complex in breast cancer cells. These effects translate into suppression of growth of a variety of ligand-independent breast cancer models including those driven by ER fusion proteins that lack the ligand binding site. The efficacy of eIF4A inhibition is enhanced when it is combined with fulvestrant--an ER degrader. Concomitant inhibition of ER synthesis and induction of its degradation causes synergistic and durable inhibition of ER expression and tumor growth. The clinical importance of these findings is confirmed by results of an early clinical trial (NCT04092673) of the selective eIF4A inhibitor zotatifin in patients with estrogen receptor positive metastatic breast cancer. Multiple clinical responses have been observed on combination therapy including durable regressions. These data suggest that eIF4A inhibition could be a useful new strategy for treating advanced ER+ breast cancer.

cancer biology↗

bioRxiv2024

APOBEC3 mutagenesis drives therapy resistance in breast cancer

Acquired genetic alterations commonly drive resistance to endocrine and targeted therapies in metastatic breast cancer1-7, however the underlying processes engendering these diverse alterations are largely uncharacterized. To identify the mutational processes operant in breast cancer and their impact on clinical outcomes, we utilized a well-annotated cohort of 3,880 patient samples with paired tumor-normal sequencing data. The mutational signatures associated with apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like 3 (APOBEC3) enzymes were highly prevalent and enriched in post-treatment compared to treatment-naive hormone receptor-positive (HR+) cancers. APOBEC3 mutational signatures were independently associated with shorter progression-free survival on antiestrogen plus CDK4/6 inhibitor combination therapy in patients with HR+ metastatic breast cancer. Whole genome sequencing (WGS) of breast cancer models and selected paired primary-metastatic samples demonstrated that active APOBEC3 mutagenesis promoted resistance to both endocrine and targeted therapies through characteristic alterations such as RB1 loss-of-function mutations. Evidence of APOBEC3 activity in pre-treatment samples illustrated a pervasive role for this mutational process in breast cancer evolution. The study reveals APOBEC3 mutagenesis to be a frequent mediator of therapy resistance in breast cancer and highlights its potential as a biomarker and target for overcoming resistance.

cancer biology↗

bioRxiv2024

Multimodal histopathologic models stratify hormone receptor-positive early breast cancer

For patients with hormone receptor-positive, early breast cancer without HER2 amplification, multigene expression assays including Oncotype DX (R) recurrence score (RS) have been clinically validated to identify patients who stand to derive added benefit from adjuvant cytotoxic chemotherapy. However, cost and turnaround time have limited its global adoption despite recommendation by practice guidelines. We investigated if routinely available hematoxylin and eosin (H&E)-stained pathology slides could act as a surrogate triaging data substrate by predicting RS using machine learning methods. We trained and validated a multimodal transformer model, Orpheus, using 6,203 patients across three independent cohorts, taking both H&E images and their corresponding synoptic text reports as input. We showed accurate inference of recurrence score from whole-slide images (r = 0.63 (95% C.I. 0.58 - 0.68); n = 1,029), the raw text of their corresponding reports (r = 0.58 (95% C.I. 0.51 - 0.64); n = 972), and their combination (r = 0.68 (95% C.I. 0.64 - 0.73); n = 964) as measured by Pearsons correlation. To predict high-risk disease (RS>25), our model achieved an area under the receiver operating characteristic curve (AUROC) of 0.89 (95% C.I. 0.83 - 0.94), and area under the precision recall curve (AUPRC) of 0.64 (95% C.I. 0.60 - 0.82), compared to 0.49 (95% C.I. 0.36 - 0.64) for an existing nomogram based on clinical and pathologic features. Moreover, our model generalizes well to external international cohorts, effectively identifying recurrence risk (r = 0.61, p < 10-4, n = 452; r = 0.60, p < 10-4, n = 575) and high-risk status (AUROC = 0.80, p < 10-4, AUPRC = 0.68, p < 10-4, n = 452; AUROC = 0.83, p < 10-4, AUPRC = 0.73, p < 10-4, n = 575) from whole-slide images. Probing the biologic underpinnings of the model decisions uncovered tumor cell size heterogeneity, immune cell infiltration, a proliferative transcription program, and stromal fraction as correlates of higher-risk predictions. We conclude that at an operating point of 94.4% precision and 33.3% recall, this model could help increase global adoption and shorten lag between resection and adjuvant therapy.

pathology↗

bioRxiv2023

Spatial molecular profiling of mixed invasive ductal-lobular breast cancers reveals heterogeneity in intrinsic molecular subtypes, oncogenic signatures and actionable driver mutations

Mixed invasive ductal and lobular carcinoma (MDLC) is a rare histologic subtype of breast cancer displaying both E-cadherin positive ductal and E-cadherin negative lobular morphologies within the same tumor, posing challenges with regard to anticipated clinical management. It remains unclear whether these distinct morphologies also have distinct biology and risk of recurrence. Our spatially-resolved transcriptomic, genomic, and single-cell profiling revealed clinically significant differences between ductal and lobular tumor regions including distinct intrinsic subtype heterogeneity (e.g., MDLC with TNBC/basal ductal and ER+/luminal lobular regions), distinct enrichment of senescence/dormancy and oncogenic (ER and MYC) signatures, genetic and epigenetic CDH1 inactivation in lobular, but not ductal regions, and single-cell ductal and lobular sub-populations with unique oncogenic signatures further highlighting intra-regional heterogeneity. Altogether, we demonstrated that the intra-tumoral morphological/histological heterogeneity within MDLC is underpinned by intrinsic subtype and oncogenic heterogeneity which may result in prognostic uncertainty and therapeutic dilemma. SignificanceMDLC displays both ductal and lobular tumor regions. Our multi-omic profiling approach revealed that these morphologically distinct tumor regions harbor distinct intrinsic subtypes and oncogenic features that may cause prognostic uncertainty and therapeutic dilemma. Thus histopathological/molecular profiling of individual tumor regions may guide clinical decision making and benefit patients with MDLC, particularly in the advanced setting where there is increased reliance on next generation sequencing.

cancer biology↗

bioRxiv2021

ERα-LBD, a novel isoform of estrogen receptor alpha, promotes breast cancer proliferation and endocrine resistance

Estrogen receptor alpha (ER) drives mammary gland development and breast cancer (BC) growth through an evolutionarily conserved linkage of DNA binding and hormone activation functions. Therapeutic targeting of the hormone binding pocket is a widely utilized and successful strategy for breast cancer prevention and treatment. However, resistance to this endocrine therapy is frequently encountered and may occur through bypass or reactivation of ER-regulated transcriptional programs. We now identify the induction of a novel ER isoform, ER-LBD, that is encoded by an alternative ESR1 transcript and lacks the activation function and DNA binding domains. Despite lacking the transcriptional activity, ER-LBD is found to promote breast cancer growth and resistance to the ER antagonist fulvestrant. ER-LBD is predominantly localized to the cytoplasm and mitochondria of BC cells and leads to enhanced glycolysis, respiration and stem-like features. Intriguingly, ER-LBD expression and function does not appear to be restricted to cancers that express full length ER but also promotes growth of triple negative breast cancers and ER-LBD transcript (ESR1-LBD) is also present in BC samples from both ER(+) and ER(-) human tumors. These findings point to ER-LBD as a potential mediator of breast cancer progression and therapy resistance. SIGNIFICANCE STATEMENTEndocrine resistant and metastatic breast cancer (BC) is a clinically significant problem. Our study of fulvestrant resistant cancer cells led to the discovery of a novel ER isoform which we call ER-LBD. Encoded by a truncated transcript variant (ESR1-LBD) and lacking the N-terminal domains (activation of transcription and DNA binding), ER-LBD displays a unique role in BC tumorigenesis and progression by mechanisms that may involve metabolic and cell growth advantages, stemness and therapy resistance. Importantly, ESR1-LBD is preferentially expressed in human breast tumor tissues and may be used as prognostic marker in BC.

cancer biology↗

bioRxiv2021

Immune and malignant cell phenotypes of ovarian cancer are determined by distinct mutational processes

High-grade serous ovarian cancer (HGSOC) is an archetypal cancer of genomic instability patterned by distinct mutational processes, intratumoral heterogeneity and intraperitoneal spread. We investigated determinants of immune recognition and evasion in HGSOC to elucidate co- evolutionary processes underlying malignant progression and tumor immunity. Mutational processes and anatomic sites of tumor foci were key determinants of tumor microenvironment cellular phenotypes, inferred from whole genome sequencing, single-cell RNA sequencing, digital histopathology and multiplexed immunofluorescence of 160 tumor sites from 42 treatment-naive HGSOC patients. Homologous recombination-deficient (HRD)-Dup (BRCA1 mutant-like) and HRD- Del (BRCA2 mutant-like) tumors harbored increased neoantigen burden, inflammatory signaling and ongoing immunoediting, reflected in loss of HLA diversity and tumor infiltration with highly- differentiated dysfunctional CD8+ T cells. Foldback inversion (FBI, non-HRD) tumors exhibited elevated TGF{beta} signaling and immune exclusion, with predominantly naive/stem-like and memory T cells. Our findings implicate distinct immune resistance mechanisms across HGSOC subtypes which can inform future immunotherapeutic strategies. HIGHLIGHTSO_LIMulti-region, multi-modal profiling of malignant and immune cell phenotypes in ovarian cancer C_LIO_LIAnatomic site specificity is a determinant of cancer cell and intratumoral immune phenotypes C_LIO_LITumor mutational processes impact mechanisms of immune control and immune evasion C_LIO_LISpatial topology of HR-deficient tumors is defined by immune interactions absent from immune inert HR-proficient subtypes C_LI

cancer biology↗