Cicatricial alopecia (CA) refers to various conditions that result in permanent hair loss. Treatment of CA has always been challenging. Regarding immune-mediated pathophysiology for many CA subtypes, ...the administration of Janus kinase (JAK) and tumor necrosis factor (TNF) inhibitors have potentiated the treatments of CA.
After a thorough systematic search in PubMed/Medline, Embase, Web of Science, Scopus, Google Scholar, ClinicalTrials.gov, and WHO ICTRP, a total of 3,532 relevant records were retrieved and screened. Accordingly, 56 studies met the eligibility criteria and entered the review.
Among JAK inhibitors, oral tofacitinib was the most frequently reported and the most effective treatment in improving signs and symptoms of CA with minimal adverse effects (AEs). Baricitinib was another JAK inhibitor with sustained improvement while causing mild AEs. As a TNF inhibitor, adalimumab induced a rapid and stable improvement in signs and symptoms in most patients with rare, tolerable AEs. Thalidomide was the other frequently reported yet controversial TNF inhibitor, which caused a rapid and significant improvement in the condition. However, it may result in mild to severe AEs, particularly neuropathies. Infliximab is a TNF inhibitor with mostly favorable results, albeit in a few patients caused treatable dermatological AEs. Apremilast and certolizumab pegol caused an incomplete amelioration of signs and symptoms with no AEs. Lenalidomide is another TNF inhibitor that can induce temporary improvement in CA with probable AEs. It is noteworthy that utilizing adalimumab, infliximab, etanercept, golimumab, and an anonymous TNF inhibitor has induced paradoxical CA and other A.E.s in some patients.
Recent studies have recommended JAK and TNF inhibitors, especially oral tofacitinib and adalimumab, as a new modality or adjuvant therapy to previous medications for primary CA. Nonetheless, monitoring AEs on a regular basis is suggested, and further extensive studies are required before definitive recommendations.
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.
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•Generation of TCGA Clinical Data Resource for 11,160 patients over 33 cancer types•Analysis of clinical outcome endpoints with usage recommendations for each cancer•Demonstration of data validity and utility for large-scale translational research
Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types.
We conducted comprehensive integrative molecular analyses of the complete set of tumors in The Cancer Genome Atlas (TCGA), consisting of approximately 10,000 specimens and representing 33 types of ...cancer. We performed molecular clustering using data on chromosome-arm-level aneuploidy, DNA hypermethylation, mRNA, and miRNA expression levels and reverse-phase protein arrays, of which all, except for aneuploidy, revealed clustering primarily organized by histology, tissue type, or anatomic origin. The influence of cell type was evident in DNA-methylation-based clustering, even after excluding sites with known preexisting tissue-type-specific methylation. Integrative clustering further emphasized the dominant role of cell-of-origin patterns. Molecular similarities among histologically or anatomically related cancer types provide a basis for focused pan-cancer analyses, such as pan-gastrointestinal, pan-gynecological, pan-kidney, and pan-squamous cancers, and those related by stemness features, which in turn may inform strategies for future therapeutic development.
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•An integrative data clustering method is applied to reclassify human tumors•Cell-of-origin influences, but does not fully determine, tumor classification•Immune features and copy-number aberrations define the most mixed tumor groups•Multi-cancer groups reveal new features with potential clinical utility
Comprehensive, integrated molecular analysis identifies molecular relationships across a large diverse set of human cancers, suggesting future directions for exploring clinical actionability in cancer treatment.
We report a comprehensive analysis of 412 muscle-invasive bladder cancers characterized by multiple TCGA analytical platforms. Fifty-eight genes were significantly mutated, and the overall mutational ...load was associated with APOBEC-signature mutagenesis. Clustering by mutation signature identified a high-mutation subset with 75% 5-year survival. mRNA expression clustering refined prior clustering analyses and identified a poor-survival “neuronal” subtype in which the majority of tumors lacked small cell or neuroendocrine histology. Clustering by mRNA, long non-coding RNA (lncRNA), and miRNA expression converged to identify subsets with differential epithelial-mesenchymal transition status, carcinoma in situ scores, histologic features, and survival. Our analyses identified 5 expression subtypes that may stratify response to different treatments.
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•Multiplatform analysis informs muscle-invasive bladder cancer subtyping•A framework associating distinct subtyping with therapeutic options•High mutational load is driven mainly by APOBEC-mediated mutagenesis•APOBEC-related mutational signature corresponds to a 75% 5-year survival
A multiplatform analysis of 412 muscle-invasive bladder cancer patients provides insights into mutational profiles with prognostic value and establishes a framework associating distinct tumor subtypes with clinical options.
We performed integrated genomic, transcriptomic, and proteomic profiling of 150 pancreatic ductal adenocarcinoma (PDAC) specimens, including samples with characteristic low neoplastic cellularity. ...Deep whole-exome sequencing revealed recurrent somatic mutations in KRAS, TP53, CDKN2A, SMAD4, RNF43, ARID1A, TGFβR2, GNAS, RREB1, and PBRM1. KRAS wild-type tumors harbored alterations in other oncogenic drivers, including GNAS, BRAF, CTNNB1, and additional RAS pathway genes. A subset of tumors harbored multiple KRAS mutations, with some showing evidence of biallelic mutations. Protein profiling identified a favorable prognosis subset with low epithelial-mesenchymal transition and high MTOR pathway scores. Associations of non-coding RNAs with tumor-specific mRNA subtypes were also identified. Our integrated multi-platform analysis reveals a complex molecular landscape of PDAC and provides a roadmap for precision medicine.
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•Multi-platform study of 150 pancreatic cancers accounting for neoplastic cellularity•Identify KRAS mutational heterogeneity and alternate drivers in KRAS wild-type tumors•Identify proteomic subtypes with prognostic significance and therapeutic implications•Integrated analysis of mRNA and non-coding RNA suggests consensus subtypes
This TCGA study reveals the complex molecular landscape of PDAC, with a small number of tumors carrying multiple KRAS mutations, KRAS wild-type PDACs harboring alterations in other RAS pathway genes or alternate oncogenic drivers, and integrated RNA and protein subtypes indicating clinically significant subsets of disease.
Our comprehensive analysis of alternative splicing across 32 The Cancer Genome Atlas cancer types from 8,705 patients detects alternative splicing events and tumor variants by reanalyzing RNA and ...whole-exome sequencing data. Tumors have up to 30% more alternative splicing events than normal samples. Association analysis of somatic variants with alternative splicing events confirmed known trans associations with variants in SF3B1 and U2AF1 and identified additional trans-acting variants (e.g., TADA1, PPP2R1A). Many tumors have thousands of alternative splicing events not detectable in normal samples; on average, we identified ≈930 exon-exon junctions (“neojunctions”) in tumors not typically found in GTEx normals. From Clinical Proteomic Tumor Analysis Consortium data available for breast and ovarian tumor samples, we confirmed ≈1.7 neojunction- and ≈0.6 single nucleotide variant-derived peptides per tumor sample that are also predicted major histocompatibility complex-I binders (“putative neoantigens”).
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•Systematic analysis of alternative splicing landscape across 8,705 cancer patients•Somatic trans-sQTL analysis identifies drivers of global splicing aberrations•Many tumors contain numerous neojunctions not typically found in normal samples•Neojunctions can be confirmed by MS and form a class of potential neoantigens
A pan-cancer analysis by Kahles et al. shows increased alternative splicing events in tumors versus normal tissue and identifies trans-acting variants associated with alternative splicing events. Tumors contain neojunction-derived peptides absent in normal samples, including predicted MHC-I binders that are putative neoantigens.
Aneuploidy, whole chromosome or chromosome arm imbalance, is a near-universal characteristic of human cancers. In 10,522 cancer genomes from The Cancer Genome Atlas, aneuploidy was correlated with ...TP53 mutation, somatic mutation rate, and expression of proliferation genes. Aneuploidy was anti-correlated with expression of immune signaling genes, due to decreased leukocyte infiltrates in high-aneuploidy samples. Chromosome arm-level alterations show cancer-specific patterns, including loss of chromosome arm 3p in squamous cancers. We applied genome engineering to delete 3p in lung cells, causing decreased proliferation rescued in part by chromosome 3 duplication. This study defines genomic and phenotypic correlates of cancer aneuploidy and provides an experimental approach to study chromosome arm aneuploidy.
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•Aneuploidy, whole chromosome or chromosome-arm imbalance, occurs in 88% of cancers•Aneuploidy correlates with cell-cycle genes and anti-correlates with immune levels•Patterns of aneuploidy alterations are tumor-type specific•Engineered chromosome 3p deletion does not promote proliferation in human lung cells
Analyzing >10,000 human cancers, Taylor et al. show that aneuploidy is correlated with somatic mutation rate, expression of proliferation genes, and decreased leukocyte infiltration. Loss of chromosome arm 3p is common in squamous cancers, but deletion of chromosome 3p reduces cell proliferation in vitro.
DNA damage repair (DDR) pathways modulate cancer risk, progression, and therapeutic response. We systematically analyzed somatic alterations to provide a comprehensive view of DDR deficiency across ...33 cancer types. Mutations with accompanying loss of heterozygosity were observed in over 1/3 of DDR genes, including TP53 and BRCA1/2. Other prevalent alterations included epigenetic silencing of the direct repair genes EXO5, MGMT, and ALKBH3 in ∼20% of samples. Homologous recombination deficiency (HRD) was present at varying frequency in many cancer types, most notably ovarian cancer. However, in contrast to ovarian cancer, HRD was associated with worse outcomes in several other cancers. Protein structure-based analyses allowed us to predict functional consequences of rare, recurrent DDR mutations. A new machine-learning-based classifier developed from gene expression data allowed us to identify alterations that phenocopy deleterious TP53 mutations. These frequent DDR gene alterations in many human cancers have functional consequences that may determine cancer progression and guide therapy.
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•DNA damage repair (DDR) gene alterations are prevalent in many human cancer types•Homology-dependent recombination (HR) and direct repair were most frequently altered•Loss of DDR function is linked to frequency and types of cancer genomic aberrations•Altered HR function can be associated with better or worse outcomes by cancer type
Knijnenburg et al. present The Cancer Genome Atlas (TCGA) Pan-Cancer analysis of DNA damage repair (DDR) deficiency in cancer. They use integrative genomic and molecular analyses to identify frequent DDR alterations across 33 cancer types, correlate gene- and pathway-level alterations with genome-wide measures of genome instability and impaired function, and demonstrate the prognostic utility of DDR deficiency scores.
Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer. Here, we describe the genomic landscape of 496 PTCs. We observed a low frequency of somatic alterations (relative to other ...carcinomas) and extended the set of known PTC driver alterations to include EIF1AX, PPM1D, and CHEK2 and diverse gene fusions. These discoveries reduced the fraction of PTC cases with unknown oncogenic driver from 25% to 3.5%. Combined analyses of genomic variants, gene expression, and methylation demonstrated that different driver groups lead to different pathologies with distinct signaling and differentiation characteristics. Similarly, we identified distinct molecular subgroups of BRAF-mutant tumors, and multidimensional analyses highlighted a potential involvement of oncomiRs in less-differentiated subgroups. Our results propose a reclassification of thyroid cancers into molecular subtypes that better reflect their underlying signaling and differentiation properties, which has the potential to improve their pathological classification and better inform the management of the disease.
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•Expanded the somatic genetic landscape of papillary thyroid cancer•Identified new cancer genes and new driver events in known cancer genes.•Signaling signatures and differentiation properties characterized across cohort•Developed a molecular classification of papillary thyroid carcinoma
A TCGA analysis of papillary thyroid carcinoma paints a nearly complete picture of its genomic drivers, reveals intriguing differences between the consequences of mutant BRAF and RAS signaling, and enables development of a scoring and classification scheme that may beneficially alter treatment courses.
Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of ...tumor-infiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment.
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•Deep learning based computational stain for staining tumor-infiltrating lymphocytes (TILs)•TIL patterns generated from 4,759 TCGA subjects (5,202 H&E slides), 13 cancer types•Computationally stained TILs correlate with pathologist eye and molecular estimates•TIL patterns linked to tumor and immune molecular features, cancer type, and outcome
Tumor-infiltrating lymphocytes (TILs) were identified from standard pathology cancer images by a deep-learning-derived “computational stain” developed by Saltz et al. They processed 5,202 digital images from 13 cancer types. Resulting TIL maps were correlated with TCGA molecular data, relating TIL content to survival, tumor subtypes, and immune profiles.
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