An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics.

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale.

Spatial molecular profiling of mixed invasive ductal and lobular breast cancers reveals heterogeneity in intrinsic molecular subtypes, oncogenic signatures, and 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 triple-negative breast cancer (TNBC) or basal ductal and estrogen receptor positive (ER+) luminal lobular regions, distinct enrichment of cell cycle arrest/senescence and oncogenic (ER and MYC) signatures, genetic and epigenetic CDH1 inactivation in lobular but not ductal regions, and single-cell ductal and lobular subpopulations with unique oncogenic signatures further highlighting intraregional heterogeneity. Altogether, we demonstrated that the intratumoral morphological/histological heterogeneity within MDLC is underpinned by intrinsic subtype and oncogenic heterogeneity which may result in prognostic uncertainty and therapeutic dilemma.

Transcriptomic congruence analysis for evaluating model organisms.

Model organisms are instrumental substitutes for human studies to expedite basic, translational, and clinical research. Despite their indispensable role in mechanistic investigation and drug development, molecular congruence of animal models to humans has long been questioned and debated. Little effort has been made for an objective quantification and mechanistic exploration of a model organism's resemblance to humans in terms of molecular response under disease or drug treatment. We hereby propose a framework, namely Congruence Analysis for Model Organisms (CAMO), for transcriptomic response analysis by developing threshold-free differential expression analysis, quantitative concordance/discordance scores incorporating data variabilities, pathway-centric downstream investigation, knowledge retrieval by text mining, and topological gene module detection for hypothesis generation. Instead of a genome-wide vague and dichotomous answer of "poorly" or "greatly" mimicking humans, CAMO assists researchers to numerically quantify congruence, to dissect true cross-species differences from unwanted biological or cohort variabilities, and to visually identify molecular mechanisms and pathway subnetworks that are best or least mimicked by model organisms, which altogether provides foundations for hypothesis generation and subsequent translational decisions.

Systems approach for congruence and selection of cancer models towards precision medicine.

Cancer models are instrumental as a substitute for human studies and to expedite basic, translational, and clinical cancer research. For a given cancer type, a wide selection of models, such as cell lines, patient-derived xenografts, organoids and genetically modified murine models, are often available to researchers. However, how to quantify their congruence to human tumors and to select the most appropriate cancer model is a largely unsolved issue. Here, we present Congruence Analysis and Selection of CAncer Models (CASCAM), a statistical and machine learning framework for authenticating and selecting the most representative cancer models in a pathway-specific manner using transcriptomic data. CASCAM provides harmonization between human tumor and cancer model omics data, systematic congruence quantification, and pathway-based topological visualization to determine the most appropriate cancer model selection. The systems approach is presented using invasive lobular breast carcinoma (ILC) subtype and suggesting CAMA1 followed by UACC3133 as the most representative cell lines for ILC research. Two additional case studies for triple negative breast cancer (TNBC) and patient-derived xenograft/organoid (PDX/PDO) are further investigated. CASCAM is generalizable to any cancer subtype and will authenticate cancer models for faithful non-human preclinical research towards precision medicine.

Research autopsy programmes in oncology: shared experience from 14 centres across the world.

While there is a great clinical need to understand the biology of metastatic cancer in order to treat it more effectively, research is hampered by limited sample availability. Research autopsy programmes can crucially advance the field through synchronous, extensive, and high-volume sample collection. However, it remains an underused strategy in translational research. Via an extensive questionnaire, we collected information on the study design, enrolment strategy, study conduct, sample and data management, and challenges and opportunities of research autopsy programmes in oncology worldwide. Fourteen programmes participated in this study. Eight programmes operated 24 h/7 days, resulting in a lower median postmortem interval (time between death and start of the autopsy, 4 h) compared with those operating during working hours (9 h). Most programmes (n = 10) succeeded in collecting all samples within a median of 12 h after death. A large number of tumour sites were sampled during each autopsy (median 15.5 per patient). The median number of samples collected per patient was 58, including different processing methods for tumour samples but also non-tumour tissues and liquid biopsies. Unique biological insights derived from these samples included metastatic progression, treatment resistance, disease heterogeneity, tumour dormancy, interactions with the tumour micro-environment, and tumour representation in liquid biopsies. Tumour patient-derived xenograft (PDX) or organoid (PDO) models were additionally established, allowing for drug discovery and treatment sensitivity assays. Apart from the opportunities and achievements, we also present the challenges related with postmortem sample collections and strategies to overcome them, based on the shared experience of these 14 programmes. Through this work, we hope to increase the transparency of postmortem tissue donation, to encourage and aid the creation of new programmes, and to foster collaborations on these unique sample collections. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Hrq1/RECQL4 regulation is critical for preventing aberrant recombination during DNA intrastrand crosslink repair and is upregulated in breast cancer.

Human RECQL4 is a member of the RecQ family of DNA helicases and functions during DNA replication and repair. RECQL4 mutations are associated with developmental defects and cancer. Although RECQL4 mutations lead to disease, RECQL4 overexpression is also observed in cancer, including breast and prostate. Thus, tight regulation of RECQL4 protein levels is crucial for genome stability. Because mammalian RECQL4 is essential, how cells regulate RECQL4 protein levels is largely unknown. Utilizing budding yeast, we investigated the RECQL4 homolog, HRQ1, during DNA crosslink repair. We find that Hrq1 functions in the error-free template switching pathway to mediate DNA intrastrand crosslink repair. Although Hrq1 mediates repair of cisplatin-induced lesions, it is paradoxically degraded by the proteasome following cisplatin treatment. By identifying the targeted lysine residues, we show that preventing Hrq1 degradation results in increased recombination and mutagenesis. Like yeast, human RECQL4 is similarly degraded upon exposure to crosslinking agents. Furthermore, over-expression of RECQL4 results in increased RAD51 foci, which is dependent on its helicase activity. Using bioinformatic analysis, we observe that RECQL4 overexpression correlates with increased recombination and mutations. Overall, our study uncovers a role for Hrq1/RECQL4 in DNA intrastrand crosslink repair and provides further insight how misregulation of RECQL4 can promote genomic instability, a cancer hallmark.

iGenSig-Rx: an integral genomic signature based white-box tool for modeling cancer therapeutic responses using multi-omics data.

Multi-omics sequencing is poised to revolutionize clinical care in the coming decade. However, there is a lack of effective and interpretable genome-wide modeling methods for the rational selection of patients for personalized interventions. To address this, we present iGenSig-Rx, an integral genomic signature-based approach, as a transparent tool for modeling therapeutic response using clinical trial datasets. This method adeptly addresses challenges related to cross-dataset modeling by capitalizing on high-dimensional redundant genomic features, analogous to reinforcing building pillars with redundant steel rods. Moreover, it integrates adaptive penalization of feature redundancy on a per-sample basis to prevent score flattening and mitigate overfitting. We then developed a purpose-built R package to implement this method for modeling clinical trial datasets. When applied to genomic datasets for HER2 targeted therapies, iGenSig-Rx model demonstrates consistent and reliable predictive power across four independent clinical trials. More importantly, the iGenSig-Rx model offers the level of transparency much needed for clinical application, allowing for clear explanations as to how the predictions are produced, how the features contribute to the prediction, and what are the key underlying pathways. We anticipate that iGenSig-Rx, as an interpretable class of multi-omics modeling methods, will find broad applications in big-data based precision oncology. The R package is available: https://github.com/wangxlab/iGenSig-Rx .

Transcriptomic analysis identifies enrichment of cAMP/PKA/CREB signaling in invasive lobular breast cancer.

OBJECTIVE: Invasive lobular breast cancer (ILC) is the most common special type of breast cancer and has unique clinicopathological and molecular hallmarks that differentiate it from the more common invasive carcinoma-no special type (NST). Despite these differences, ILC and NST are treated as a single entity and there is a lack of ILC-targeted therapies. To fill this gap, we sought to identify novel molecular alterations in ILC that could be exploited for targeted therapies. METHODS: Differential gene expression and Geneset Enrichment and Variation analyses were performed on RNA-seq data from three large public breast cancer databases-the Sweden Cancerome Analysis Network-Breast (SCAN-B; luminal A ILC N = 263, luminal A NST N = 1162), The Cancer Genome Atlas (TCGA; luminal A ILC N = 157, luminal A NST N = 307) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC; luminal A ILC N = 65, luminal A NST N = 533). Pathways enriched in overlapping differentially expressed genes from these datasets were clustered using Jaccard similarity to identify pathways enriched in ILC. The cAMP/PKA/CREB signaling was studied in ILC, ILC-like and NST cell lines and patient-derived organoids (PDOs) using forskolin, an activator of the pathway. RESULTS: Clinicopathological features of patients with ILC and NST in SCAN-B were similar to prior population-based studies. There was a consistent pattern of up-regulation of cAMP/PKA/CREB related signaling in ILC compared to NST in SCAN-B, TCGA and METABRIC. Treatment with forskolin resulted in a greater increase in phospho-CREB in ILC cell lines and organoids than NST. CRISPR deletion of CDH1 in NST cell lines did not alter response of cells to forskolin as measured by phospho-CREB. Forskolin treatment caused growth inhibition in ILC and NST, with ILC cell lines being more sensitive to forskolin-mediated growth inhibition. CONCLUSION: In three separate datasets, cAMP/PKA/CREB signaling was identified to be higher in ILC than NST. This in silico finding was validated in cell line and organoid models. Loss of CDH1 was not sufficient to mediate this phenotype. Future studies should investigate the mechanisms for differential cAMP/PKA/CREB signaling and the potential for therapeutic targeting in patients with ILC.

Highlight of 2023: CAR T cells driving precision therapy for autoimmune disease.

CAR T cell therapy is showing remarkable results in autoimmune disease with treatment-refractory patients showing durable drug-free remission. Here, we highlight five key papers from 2023 that are driving the development of CAR T cells to improve precision, safety, efficacy and accessibility for the treatment of autoantibody-associated autoimmune diseases.

Liver tropism of ER mutant breast cancer is characterized by unique molecular changes and immune infiltration.

PURPOSE: Hotspot estrogen receptor alpha (ER/ESR1) mutations are recognized as the driver for both endocrine resistance and metastasis in advanced ER-positive (ER+) breast cancer, but their contributions to metastatic organ tropism remain insufficiently understood. In this study, we aim to comprehensively profile the organotropic metastatic pattern for ESR1 mutant breast cancer. METHODS: The organ-specific metastatic pattern of ESR1 mutant breast cancer was delineated using multi-omics data from multiple publicly available cohorts of ER+ metastatic breast cancer patients. Gene mutation/copy number variation (CNV) and differential gene expression analyses were performed to identify the genomic and transcriptomic alterations uniquely associated with ESR1 mutant liver metastasis. Upstream regulator, downstream pathway, and immune infiltration analysis were conducted for subsequent mechanistic investigations. RESULTS: ESR1 mutation-driven liver tropism was revealed by significant differences, encompassing a higher prevalence of liver metastasis in patients with ESR1 mutant breast cancer and an enrichment of mutations in liver metastatic samples. The significant enrichment of AGO2 copy number amplifications (CNAs) and multiple gene expression changes were revealed uniquely in ESR1 mutant liver metastasis. We also unveiled alterations in downstream signaling pathways and immune infiltration, particularly an enrichment of neutrophils, suggesting potential therapeutic vulnerabilities. CONCLUSION: Our data provide a comprehensive characterization of the behaviors and mechanisms of ESR1 mutant liver metastasis, paving the way for the development of personalized therapy to target liver metastasis for patients with ESR1 mutant breast cancer.

Children with developmental dyslexia have equivalent audiovisual speech perception performance but their perceptual weights differ.

As reading is inherently a multisensory, audiovisual (AV) process where visual symbols (i.e., letters) are connected to speech sounds, the question has been raised whether individuals with reading difficulties, like children with developmental dyslexia (DD), have broader impairments in multisensory processing. This question has been posed before, yet it remains unanswered due to (a) the complexity and contentious etiology of DD along with (b) lack of consensus on developmentally appropriate AV processing tasks. We created an ecologically valid task for measuring multisensory AV processing by leveraging the natural phenomenon that speech perception improves when listeners are provided visual information from mouth movements (particularly when the auditory signal is degraded). We designed this AV processing task with low cognitive and linguistic demands such that children with and without DD would have equal unimodal (auditory and visual) performance. We then collected data in a group of 135 children (age 6.5-15) with an AV speech perception task to answer the following questions: (1) How do AV speech perception benefits manifest in children, with and without DD? (2) Do children all use the same perceptual weights to create AV speech perception benefits, and (3) what is the role of phonological processing in AV speech perception? We show that children with and without DD have equal AV speech perception benefits on this task, but that children with DD rely less on auditory processing in more difficult listening situations to create these benefits and weigh both incoming information streams differently. Lastly, any reported differences in speech perception in children with DD might be better explained by differences in phonological processing than differences in reading skills. RESEARCH HIGHLIGHTS: Children with versus without developmental dyslexia have equal audiovisual speech perception benefits, regardless of their phonological awareness or reading skills. Children with developmental dyslexia rely less on auditory performance to create audiovisual speech perception benefits. Individual differences in speech perception in children might be better explained by differences in phonological processing than differences in reading skills.

Genomic selection for crop improvement in fruits and vegetables: a systematic scoping review.

To ensure the nutritional needs of an expanding global population, it is crucial to optimize the growing capabilities and breeding values of fruit and vegetable crops. While genomic selection, initially implemented in animal breeding, holds tremendous potential, its utilization in fruit and vegetable crops remains underexplored. In this systematic review, we reviewed 63 articles covering genomic selection and its applications across 25 different types of fruit and vegetable crops over the last decade. The traits examined were directly related to the edible parts of the crops and carried significant economic importance. Comparative analysis with WHO/FAO data identified potential economic drivers underlying the study focus of some crops and highlighted crops with potential for further genomic selection research and application. Factors affecting genomic selection accuracy in fruit and vegetable studies are discussed and suggestions made to assist in their implementation into plant breeding schemes. Genetic gain in fruits and vegetables can be improved by utilizing genomic selection to improve selection intensity, accuracy, and integration of genetic variation. However, the reduction of breeding cycle times may not be beneficial in crops with shorter life cycles such as leafy greens as compared to fruit trees. There is an urgent need to integrate genomic selection methods into ongoing breeding programs and assess the actual genomic estimated breeding values of progeny resulting from these breeding programs against the prediction models. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-024-01497-2.

Anti-reflection coating with mullite and Duroid for large-diameter cryogenic sapphire and alumina optics.

We developed a broadband two-layer anti-reflection (AR) coating for use on a sapphire half-wave plate (HWP) and an alumina infrared (IR) filter for the cosmic microwave background (CMB) polarimetry. Measuring the faint CMB B-mode signals requires maximizing the number of photons reaching the detectors and minimizing spurious polarization due to reflection with an off-axis incident angle. Sapphire and alumina have high refractive indices of 3.1 and are highly reflective without an AR coating. This paper presents the design, fabrication, quality control, and measured performance of an AR coating using thermally sprayed mullite and Duroid 5880LZ. This technology enables large optical elements with diameters of 600 mm. We also present a thermography-based nondestructive quality control technique, which is key to assuring good adhesion and preventing delamination when thermal cycling. We demonstrate the average reflectance of about 2.6% (0.9%) for two observing bands centered at 90/150 (220/280) GHz. At room temperature, the average transmittance of a 105 mm square test sample at 220/280 GHz is 83%, and it will increase to 90% at 100 K, attributed to reduced absorption losses. Therefore, our developed layering technique has proved effective for 220/280 GHz applications, particularly in addressing dielectric loss concerns. This AR coating technology has been deployed in the cryogenic HWP and IR filters of the Simons Array and the Simons observatory experiments and applies to future experiments such as CMB-S4.

The diagnosis and misdiagnosis of Sjögren disease.

Although one of the most common systemic autoimmune disorders, Sjögren disease (SjD) may be overlooked in patients presenting with non-specific symptoms or no complaints of sicca symptoms. SjD is not a condition to be missed as patients could present with serious extra-glandular manifestations, including lymphomas. In this article, we discuss the diagnostic pitfalls of this disorder and encourage physicians to consider carefully the 'non-textbook' presentations.

Comparing narrative storytelling ability in individuals with autism and fetal alcohol spectrum disorders.

BACKGROUND: Narrative discourse, or storytelling, is used in daily conversation and requires higher-level language and social communication skills that are not always captured by standardised assessments of language. Many autistic individuals and individuals with fetal alcohol spectrum disorders (FASD) have difficulties with both social communication and language skills, and narrative discourse analysis offers an ecologically relevant approach to assessing those challenges. AIMS: This study investigated narrative discourse in individuals with autism and FASD, as well as an age- and sex-matched comparison group. METHODS AND PROCEDURES: Narratives from 45 adolescents and adults, 11 with autism, 11 with FASD and 23 age- and sex-matched comparison participants were elicited using a wordless storybook. They were then transcribed orthographically, formatted to the Systematic Analyses of Language Transcript (SALT) convention and scored based on the SALT Narrative Scoring Scheme (NSS), a standardised language analysis protocol. In addition to the NSS total score, which assesses the overall structure and cohesion of the narratives produced, local and global measures of language ability were also employed. The local language measures included the number of mental state and temporal relation terms produced, while the global language measures included mean length of utterance, total different words, total words, total utterances, rate of speech, the number of mazes (e.g., repetitions, 'um', 'uh' or self-corrections) per total word and the NSS total score. OUTCOMES AND RESULTS: Using the SALT Language Sample Analysis tool, our results revealed that on global language measures, group differences were found on rate of speech, number of mazes per total words and the description of conflict/resolution in the narratives produced. The autism group produced significantly more mazes per total word and scored higher on the NSS conflict/resolution category score compared to the FASD and comparison groups. Both the autism and FASD groups spoke at a lower rate than the comparison group. On local language measures of narrative production, all groups were comparable, on average. CONCLUSIONS AND IMPLICATIONS: While many aspects of narrative discourse in the autism and FASD groups were similar to each other and to the comparison group, we observed group differences on global measures of narrative production and significant individual variability within groups, suggesting that narrative abilities considered at an individual level may provide important clinical information for intervention planning. Future research should also consider additional variables that influence narrative discourse, such as motivation, distractibility or decision-making of individual participants. WHAT THIS PAPER ADDS: What is already known on the subject Narrative discourse, or storytelling, is used in daily conversational interactions and reveals higher-level language skills that may not be well captured by standardised assessments of language. Many autistic individuals and individuals with fetal alcohol spectrum disorders (FASD) show difficulty with pragmatic and expressive language skills. What this paper adds to existing knowledge We found that many aspects of the narratives produced by the adolescents/young adults in the autism and FASD groups were comparable to each other and to the neurotypical group. However, the groups differed on three global measures of narrative production: rate of speech, number of mazes per total words and the description of conflict/resolution in the narratives produced. Also, significant variability was observed within groups, suggesting that narrative abilities should be considered at an individual level as opposed to their clinical groups. What are the potential or actual clinical implications of this work? This study showed that narrative discourse is an appropriate task that can be added to routine clinical assessments of language abilities in autistic adolescents/young adults as well as those with FASD or typical development and has the potential to reveal higher-level, real-world language skills. An important clinical implication of this study is that narrative language abilities should be considered at an individual level and individual-tailored interventions based on ability level due to the variability observed across individuals.

RET signaling in breast cancer therapeutic resistance and metastasis.

RET, a single-pass receptor tyrosine kinase encoded on human chromosome 10, is well known to the field of developmental biology for its role in the ontogenesis of the central and enteric nervous systems and the kidney. In adults, RET alterations have been characterized as drivers of non-small cell lung cancer and multiple neuroendocrine neoplasms. In breast cancer, RET signaling networks have been shown to influence diverse functions including tumor development, metastasis, and therapeutic resistance. While RET is known to drive the development and progression of multiple solid tumors, therapeutic agents selectively targeting RET are relatively new, though multiple multi-kinase inhibitors have shown promise as RET inhibitors in the past; further, RET has been historically neglected as a potential therapeutic co-target in endocrine-refractory breast cancers despite mounting evidence for a key pathologic role and repeated description of a bi-directional relationship with the estrogen receptor, the principal driver of most breast tumors. Additionally, the recent discovery of RET enrichment in breast cancer brain metastases suggests a role for RET inhibition specific to advanced disease. This review assesses the status of research on RET in breast cancer and evaluates the therapeutic potential of RET-selective kinase inhibitors across major breast cancer subtypes.

CDKN2A/B Homozygous Deletions in Astrocytomas: A Literature Review.

Genomic alterations of CDKN2A and CDKN2B in astrocytomas have been an evolving area of study for decades. Most recently, there has been considerable interest in the effect of CDKN2A and/or CDKN2B (CDKN2A/B) homozygous deletions (HD) on the prognosis of isocitrate dehydrogenase (IDH)-mutant astrocytomas. This is highlighted by the adoption of CDKN2A/B HD as an essential criterion for astrocytoma and IDH-mutant central nervous system (CNS) WHO grade 4 in the fifth edition of the World Health Organisation (WHO) Classification of Central Nervous System Tumours (2021). The CDKN2A and CDKN2B genes are located on the short arm of chromosome 9. CDKN2A encodes for two proteins, p14 and p16, and CDKN2B encodes for p15. These proteins regulate cell growth and angiogenesis. Interpreting the impact of CDKN2A/B alterations on astrocytoma prognosis is complicated by recent changes in tumour classification and a lack of uniform standards for testing CDKN2A/B. While the prognostic impact of CDKN2A/B HD is established, the role of different CDKN2A/B alterations-heterozygous deletions (HeD), point mutations, and promoter methylation-is less clear. Consequently, how these alternations should be incorporated into patient management remains controversial. To this end, we reviewed the literature on different CDKN2A/B alterations in IDH-mutant astrocytomas and their impact on diagnosis and management. We also provided a historical review of the changing impact of CDKN2A/B alterations as glioma classification has evolved over time. Through this historical context, we demonstrate that CDKN2A/B HD is an important negative prognostic marker in IDH-mutant astrocytomas; however, the historical data is challenging to interpret given changes in tumour classification over time, variation in the quality of evidence, and variations in the techniques used to identify CDKN2A/B deletions. Therefore, future prospective studies using uniform classification and detection techniques are required to improve the clinical interpretation of this molecular marker.

Mixed invasive ductal lobular carcinoma is clinically and pathologically more similar to invasive lobular than ductal carcinoma.

BACKGROUND: Mixed invasive ductal lobular carcinoma (mDLC) remains a poorly understood subtype of breast cancer composed of coexisting ductal and lobular components. METHODS: We sought to describe clinicopathologic characteristics and determine whether mDLC is clinically more similar to invasive ductal carcinoma (IDC) or invasive lobular carcinoma (ILC), using data from patients seen at the University of Pittsburgh Medical Center. RESULTS: We observed a higher concordance in clinicopathologic characteristics between mDLC and ILC, compared to IDC. There is a trend for higher rates of successful breast-conserving surgery after neoadjuvant chemotherapy in patients with mDLC compared to patients with ILC, in which it is known to be lower than in those with IDC. Metastatic patterns of mDLC demonstrate a propensity to develop in sites characteristic of both IDC and ILC. A meta-analysis evaluating mDLC showed shared features with both ILC and IDC with significantly more ER-positive and fewer high grades in mDLC compared to IDC, although mDLCs were significantly smaller and included fewer late-stage tumours compared to ILC. CONCLUSIONS: These findings support clinicopathologic characteristics of mDLC driven by individual ductal vs lobular components and given the dominance of lobular pathology, mDLC features are often more similar to ILC than IDC. This study exemplifies the complexity of mixed disease.

Semi-deconvolution of bulk and single-cell RNA-seq data with application to metastatic progression in breast cancer.

MOTIVATION: Identifying cell types and their abundances and how these evolve during tumor progression is critical to understanding the mechanisms of metastasis and identifying predictors of metastatic potential that can guide the development of new diagnostics or therapeutics. Single-cell RNA sequencing (scRNA-seq) has been especially promising in resolving heterogeneity of expression programs at the single-cell level, but is not always feasible, e.g. for large cohort studies or longitudinal analysis of archived samples. In such cases, clonal subpopulations may still be inferred via genomic deconvolution, but deconvolution methods have limited ability to resolve fine clonal structure and may require reference cell type profiles that are missing or imprecise. Prior methods can eliminate the need for reference profiles but show unstable performance when few bulk samples are available. RESULTS: In this work, we develop a new method using reference scRNA-seq to interpret sample collections for which only bulk RNA-seq is available for some samples, e.g. clonally resolving archived primary tissues using scRNA-seq from metastases. By integrating such information in a Quadratic Programming framework, our method can recover more accurate cell types and corresponding cell type abundances in bulk samples. Application to a breast tumor bone metastases dataset confirms the power of scRNA-seq data to improve cell type inference and quantification in same-patient bulk samples. AVAILABILITY AND IMPLEMENTATION: Source code is available on Github at https://github.com/CMUSchwartzLab/RADs.

Sound Level Changes the Auditory Cortical Activation Detected with Functional Near-Infrared Spectroscopy.

BACKGROUND: Functional near-infrared spectroscopy (fNIRS) is a viable non-invasive technique for functional neuroimaging in the cochlear implant (CI) population; however, the effects of acoustic stimulus features on the fNIRS signal have not been thoroughly examined. This study examined the effect of stimulus level on fNIRS responses in adults with normal hearing or bilateral CIs. We hypothesized that fNIRS responses would correlate with both stimulus level and subjective loudness ratings, but that the correlation would be weaker with CIs due to the compression of acoustic input to electric output. METHODS: Thirteen adults with bilateral CIs and 16 with normal hearing (NH) completed the study. Signal-correlated noise, a speech-shaped noise modulated by the temporal envelope of speech stimuli, was used to determine the effect of stimulus level in an unintelligible speech-like stimulus between the range of soft to loud speech. Cortical activity in the left hemisphere was recorded. RESULTS: Results indicated a positive correlation of cortical activation in the left superior temporal gyrus with stimulus level in both NH and CI listeners with an additional correlation between cortical activity and perceived loudness for the CI group. The results are consistent with the literature and our hypothesis. CONCLUSIONS: These results support the potential of fNIRS to examine auditory stimulus level effects at a group level and the importance of controlling for stimulus level and loudness in speech recognition studies. Further research is needed to better understand cortical activation patterns for speech recognition as a function of both stimulus presentation level and perceived loudness.