Biology subjects

Janes, K.

Publications and source records attributed to Janes, K..

7 recordsLinked to original sources

bioRxiv2025

Fast, flexible, learning-free organoid quantification and tracking with OrganoSeg2

Organoids are routinely imaged by brightfield microscopy at low magnification, but these images are challenging to analyze quantitatively at scale. Given differences in organoid-culture format and image acquisition among research groups, there is a general need for versatile segmentation algorithms that refine for specific applications. Here, we introduce OrganoSeg2, an overhauled software that substantively advances the multi-window adaptive thresholding of its predecessor. OrganoSeg2 gives users access to additional segmentation parameters that were latent in OrganoSeg, and common operations are accelerated [~]10-fold. Using data from six organoid types, we find that the generalized segmentation accuracy of OrganoSeg2 surpasses multiple alternatives, including segmenters based on deep learning. OrganoSeg2 adds longitudinal single-organoid tracking and multicolor fluorescence quantification, which we use to examine growth trajectories and radiotherapy responses in luminal breast cancer organoids. OrganoSeg2 is shared freely as installation packages for current users and source code for future developers (https://github.com/JanesLab/OrganoSeg2). MOTIVATIONOrganoids are routinely documented with low-magnification brightfield and fluorescence images that are challenging to quantify accurately in large numbers. OrganoSeg2 is a streamlined, highly customizable segmenter that surpasses its prior version and AI-themed competitors in various organoid contexts. New longitudinal tracking and fluorescence capabilities of OrganoSeg2 are demonstrated with experiments investigating the cell-death responses of luminal breast cancer organoids to radiotherapy.

bioengineering↗

bioRxiv2025

PCSK5M452I is a recessive hypomorph exclusive to MCF10DCIS.com cells

The most widely used cell line for studying ductal carcinoma in situ (DCIS) premalignancy is the transformed breast epithelial cell line, MCF10DCIS.com. During its original clonal isolation and selection, MCF10DCIS.com acquired a heterozygous M452I mutation in the proprotein convertase PCSK5, which has never been reported in any human cancer. The mutation is noteworthy because PCSK5 matures GDF11, a TGF{beta}-superfamily ligand that suppresses progression of triple-negative breast cancer. We asked here whether PCSK5M452I and its activity toward GDF11 might contribute to the unique properties of MCF10DCIS.com. Using an optimized in-cell GDF11 maturation assay, we found that overexpressed PCSK5M452I was measurably active but at a fraction of the wildtype enzyme. In a PCSK5-/- clone of MCF10DCIS.com reconstituted with different PCSK5 alleles, PCSK5M452I was mildly defective in anterograde transport. However, the multicellular organization of PCSK5M452I addback cells in 3D matrigel cultures was significantly less compact than wildtype and indistinguishable from a PCSK5T288P null allele. Growth of intraductal MCF10DCIS.com xenografts was similarly impaired along with the frequency of comedo necrosis and stromal activation. In no setting did PCSK5M452I exhibit gain-of-function activity, leading us to conclude that it is hypomorphic and thus compensated by the remaining wildtype allele in MCF10DCIS.com. ImplicationsThis work reassures that an exotic PCSK5 mutation is not responsible for the salient characteristics of the MCF10DCIS.com cell line.

cancer biology↗

bioRxiv2024

Patient-derived response estimates from zero-passage organoids of luminal breast cancer

BackgroundPrimary luminal breast cancer cells lose their identity rapidly in standard tissue culture, which is problematic for testing hormone interventions and molecular pathways specific to the luminal subtype. Breast cancer organoids are thought to retain tumor characteristics better, but long-term viability of luminal-subtype cases is a persistent challenge. Our goal was to adapt short-term organoids of luminal breast cancer for parallel testing of genetic and pharmacologic perturbations. MethodsWe freshly isolated patient-derived cells from luminal tumor scrapes, miniaturized the organoid format into 5 {micro}l replicates for increased throughput, and set an endpoint of 14 days to minimize drift. Therapeutic hormone targeting was mimicked in these "zero-passage" organoids by withdrawing {beta}-estradiol and adding 4-hydroxytamoxifen. We also examined sulforaphane as an electrophilic stress and commercial neutraceutical with reported anti-cancer properties. Downstream mechanisms were tested genetically by lentiviral transduction of two complementary sgRNAs and Cas9 stabilization for the first week of organoid culture. Transcriptional changes were measured by RT-qPCR or RNA sequencing, and organoid phenotypes were quantified by serial brightfield imaging, digital image segmentation, and regression modeling of cellular doubling times. ResultsWe achieved >50% success in initiating luminal breast cancer organoids from tumor scrapes and maintaining them to the 14-day zero-passage endpoint. Success was mostly independent of clinical parameters, supporting general applicability of the approach. Abundance of ESR1 and PGR in zero-passage organoids consistently remained within the range of patient variability at the endpoint. However, responsiveness to hormone withdrawal and blockade was highly variable among luminal breast cancer cases tested. Combining sulforaphane with knockout of NQO1 (a phase II antioxidant response gene and downstream effector of sulforaphane) also yielded a breadth of organoid growth phenotypes, including growth inhibition with sulforaphane, growth promotion with NQO1 knockout, and growth antagonism when combined. ConclusionsZero-passage organoids are a rapid and scalable way to interrogate properties of luminal breast cancer cells from patient-derived material. This includes testing drug mechanisms of action in different clinical cohorts. A future goal is to relate inter-patient variability of zero-passage organoids to long-term outcomes.

cancer biology↗

bioRxiv2020

Pan-cancer Drivers are Recurrent Transcriptional Regulatory Heterogeneities in Early-stage Luminal Breast Cancer

The heterogeneous composition of solid tumors is known to impact disease progression and response to therapy. Malignant cells coexist in different regulatory states that can be accessed transcriptomically by single-cell RNA sequencing, but these methods have many caveats related to sensitivity, noise, and sample handling. We revised a statistical fluctuation analysis called stochastic profiling to combine with 10-cell RNA sequencing, which was designed for laser-capture microdissection (LCM) and extended here for immuno-LCM. When applied to a cohort of late-onset, early-stage luminal breast cancers, the integrated approach identified thousands of candidate regulatory heterogeneities. Intersecting the candidates from different tumors yielded a relatively stable set of 710 recurrent heterogeneously expressed genes (RHEGs) that were significantly variable in >50% of patients. RHEGs were not strongly confounded by dissociation artifacts, cell cycle oscillations, or driving mutations for breast cancer. Rather, we detected RHEG enrichments for epithelial-to-mesenchymal transition genes and, unexpectedly, the latest pan-cancer assembly of driver genes across cancer types other than breast. Heterogeneous transcriptional regulation conceivably provides a faster, reversible mechanism for malignant cells to evaluate the effects of potential oncogenes or tumor suppressors on cancer hallmarks. Statement of significanceProfiling intratumor heterogeneity of luminal breast carcinoma cells identifies a recurrent set of genes suggesting sporadic activation of pathways known to drive other types of cancer.

cancer biology↗

bioRxiv2020

Fragmentation of Small-cell Lung Cancer Regulatory States in Heterotypic Microenvironments

Small-cell lung cancers derive from pulmonary neuroendocrine cells, which have stemlike properties to reprogram into other cell types upon lung injury. It is difficult to uncouple transcriptional plasticity of these transformed cells from genetic changes that evolve in primary tumors or secondary metastases. Profiling of single cells also problematic if the required sample dissociation activates injury-like signaling and reprogramming. Here, we defined cell-state heterogeneities in situ through laser capture microdissection-based 10-cell transcriptomics coupled with stochastic-profiling fluctuation analysis. Using labeled cells from a small-cell lung cancer mouse model initiated by neuroendocrine deletion of Rb1-Trp53, we profiled variations in transcript abundance to identify cell-to-cell differences in regulatory state in vitro and in vivo. Fluctuating transcripts in spheroid culture were partly shared among Rb1-Trp53-null models, and heterogeneities increased considerably when cells were delivered intravenously to colonize the liver. Colonization of immunocompromised animals drove fractional appearance of alveolar type II-like markers and poised cells for paracrine stimulation from immune cells and hepatocytes. Immunocompetency further exaggerated the fragmentation of tumor states in the liver, yielding mixed stromal signatures evident in bulk sequencing from autochthonous tumors and metastases. Dozens of transcript heterogeneities recur irrespective of biological context; their mapped orthologs brought together observations of murine and human small-cell lung cancer. Candidate heterogeneities recurrent in the liver also stratified primary human tumors into discrete groups not readily explained by molecular subtype but with prognostic relevance. We conclude that heterotypic interactions in the liver and lung are an accelerant for intratumor heterogeneity in small-cell lung cancer. Statement of significanceThe single-cell regulatory heterogeneity of small-cell lung cancer becomes increasingly elaborate in the liver, a common metastatic site for the disease.

cancer biology↗

bioRxiv2020

Single-cell Bottlenecks and Dead-ends During Glioma Premalignancy

Cancer evolves from premalignant clones that accumulate mutations and adopt unusual cell states to achieve transformation. Previously, we pinpointed the oligodendrocyte precursor cell (OPC) as a cell-of-origin for glioma, but the early changes of mutant OPCs during premalignancy remained unknown. Using mice engineered for inducible Nf1-Trp53 loss in OPCs, we acutely isolated labeled mutant OPCs by laser-capture microdissection and determined gene-expression changes by bulk RNA sequencing and a fluctuation analysis, called stochastic profiling, which uses RNA-sequencing measurements from random pools of 10 mutant cells. At 12 days after Nf1-Trp53 deletion, while bulk differences were mostly limited to mitotic hallmarks and genes for ribosome biosynthesis, stochastic profiling revealed a spectrum of stem-progenitor (Axl, Aldh1a1), proneural, and mesenchymal states as potential starting points for gliomagenesis. At 90 days, bulk sequencing detected very few differentially expressed transcripts, whereas stochastic profiling revealed cell states for neurons and mural cells that do not give rise to glial tumors, suggesting cellular dead-ends for gliomagenesis. Importantly, we identified mutant OPCs that strongly expressed key effectors of nonsense-mediated decay (Upf3b) and homology-dependent DNA repair (Rad51c, Slx1b, Ercc4) along with DNA-damage markers suggesting transcription-associated replication stress. Analysis of 10-cell transcriptomes at 90 days identified a locus of elevated gene expression containing an additional repair endonuclease (Mus81) and Rin1, a Ras-Raf antagonist and possible counterbalance to Nf1 loss. At 150 days, Rin1 was microdeleted in some gliomas and downregulated in all others. Replication stress may pose a considerable bottleneck that must be resolved for gliomas to initiate. Statement of significanceIn situ stochastic profiling of heterogeneous cell states in a mouse model of glioma uncovers regulatory confusion in a glioma cell-of-origin and defines a state of replication stress that precedes tumor initiation.

cancer biology↗

bioRxiv2019

Sporadic activation of an oxidative stress-dependent NRF2-p53 signaling network in breast epithelial spheroids and premalignancies

Breast-mammary epithelial cells experience different local environments during tissue development and tumorigenesis. Microenvironmental heterogeneity gives rise to distinct cell-regulatory states whose identity and importance are just beginning to be appreciated. Cellular states diversify when clonal 3D spheroids are cultured in basement membrane, and prior transcriptomic analyses identified a state associated with stress tolerance and poor response to anticancer therapeutics. Here, we examined the regulation of this state and found that it is jointly coordinated by the NRF2 and p53 pathways, which are co-stabilized by spontaneous oxidative stress within the 3D cultures. Inhibition of NRF2 or p53 individually disrupts some of the transcripts defining the regulatory state but does not yield a notable phenotype in nontransformed breast epithelial cells. In contrast, combined perturbation prevents 3D growth in an oxidative stress-dependent manner. By integrating systems models of NRF2 and p53 signaling together as a single oxidative-stress network, we recapitulate these observations and make predictions about oxidative stress profiles during 3D growth. Similar coordination of NRF2 and p53 signaling is observed in normal breast epithelial tissue and hormone-negative ductal carcinoma in situ lesions. However, the pathways are uncoupled in triple-negative breast cancer, a subtype in which p53 is usually mutated. Using the integrated model, we reconcile the different NRF2-knockdown phenotypes of triple-negative cancer lines with their inferred handling of oxidative stress. Our results point to an oxidative stress-tolerance network that is important for single cells during glandular development and the early stages of breast cancer. One Sentence SummaryReactive oxygen species co-stabilize a non-oncogene and a tumor suppressor for triple-negative breast cancer when cells are surrounded by basement-membrane ECM.

cancer biology↗