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At least 343 records · Page 19Linked to original sources
PubMed2005

A molecular signature in superficial bladder carcinoma predicts clinical outcome.

PURPOSE: Cancer of the urinary bladder is a common malignant disease in the western countries. The majority of patients presents with superficial tumors with a high recurrence frequency, a minor fraction of these patients experience disease progression to a muscle invasive stage. No clinical useful molecular markers exist to identify patients showing later disease progression. The purpose of this study was to identify markers of disease progression using full-genome expression analysis. EXPERIMENTAL DESIGN: We did a full-genome expression analysis (59,619 genes and expressed sequence tags) of superficial bladder tumors from 29 bladder cancer patients (13 without later disease progression and 16 with later disease progression) using high-density oligonucleotide microarrays. We used supervised learning for identification of the optimal genes for predicting disease progression. The identified genes were validated on an independent test set (74 superficial tumor samples) using in house-fabricated 60-mer oligonucleotide microarrays. RESULTS: We identified a 45-gene signature of disease progression. By monitoring this progression signature in an independent test set, we found a significant correlation between our classifications and the clinical outcome (P < 0.03). The genes identified as differentially expressed were involved in regulating apoptosis, cell differentiation, and cell cycle and hence may represent potential therapeutic targets. CONCLUSIONS: Our results indicate that it may be possible to identify patients with a high risk of disease progression at an early stage using a molecular signature present already in the superficial tumors. In this way, better treatment and follow-up regimens could be assigned to patients suffering from superficial bladder cancer.

Cluster Analysis↗
PubMed2005

Microarray analysis identifies a death-from-cancer signature predicting therapy failure in patients with multiple types of cancer.

Activation in transformed cells of normal stem cells' self-renewal pathways might contribute to the survival life cycle of cancer stem cells and promote tumor progression. The BMI-1 oncogene-driven gene expression pathway is essential for the self-renewal of hematopoietic and neural stem cells. We applied a mouse/human comparative translational genomics approach to identify an 11-gene signature that consistently displays a stem cell-resembling expression profile in distant metastatic lesions as revealed by the analysis of metastases and primary tumors from a transgenic mouse model of prostate cancer and cancer patients. To further validate these results, we examined the prognostic power of the 11-gene signature in several independent therapy-outcome sets of clinical samples obtained from 1,153 cancer patients diagnosed with 11 different types of cancer, including 5 epithelial malignancies (prostate, breast, lung, ovarian, and bladder cancers) and 5 nonepithelial malignancies (lymphoma, mesothelioma, medulloblastoma, glioma, and acute myeloid leukemia). Kaplan-Meier analysis demonstrated that a stem cell-like expression profile of the 11-gene signature in primary tumors is a consistent powerful predictor of a short interval to disease recurrence, distant metastasis, and death after therapy in cancer patients diagnosed with 11 distinct types of cancer. These data suggest the presence of a conserved BMI-1-driven pathway, which is similarly engaged in both normal stem cells and a highly malignant subset of human cancers diagnosed in a wide range of organs and uniformly exhibiting a marked propensity toward metastatic dissemination as well as a high probability of unfavorable therapy outcome.

Animals↗
PubMed2005

A cancer-specific transcriptional signature in human neoplasia.

The molecular anatomy of cancer cells is being explored through unbiased approaches aimed at the identification of cancer-specific transcriptional signatures. An alternative biased approach is exploitation of molecular tools capable of inducing cellular transformation. Transcriptional signatures thus identified can be readily validated in real cancers and more easily reverse-engineered into signaling pathways, given preexisting molecular knowledge. We exploited the ability of the adenovirus early region 1 A protein (E1A) oncogene to force the reentry into the cell cycle of terminally differentiated cells in order to identify and characterize genes whose expression is upregulated in this process. A subset of these genes was activated through a retinoblastoma protein/E2 viral promoter required factor-independent (pRb/E2F-independent) mechanism and was overexpressed in a fraction of human cancers. Furthermore, this overexpression correlated with tumor progression in colon cancer, and 2 of these genes predicted unfavorable prognosis in breast cancer. A proof of principle biological validation was performed on one of the genes of the signature, skeletal muscle cell reentry-induced (SKIN) gene, a previously undescribed gene. SKIN was found overexpressed in some primary tumors and tumor cell lines and was amplified in a fraction of colon adenocarcinomas. Furthermore, knockdown of SKIN caused selective growth suppression in overexpressing tumor cell lines but not in tumor lines expressing physiological levels of the transcript. Thus, SKIN is a candidate oncogene in human cancer.

Adenovirus E1A Proteins↗
PubMed2005

NFkappaB activity, function, and target-gene signatures in primary mediastinal large B-cell lymphoma and diffuse large B-cell lymphoma subtypes.

Primary mediastinal large B-cell lymphoma (MLBCL) shares important clinical and molecular features with classic Hodgkin lymphoma, including nuclear localization of the nuclear factor kappaB (NFkappaB) subunit c-REL (reticuloendotheliosis viral oncogene homolog) in a pilot series. Herein, we analyzed c-REL subcellular localization in additional primary MLBCLs and characterized NFkappaB activity and function in a MLBCL cell line. The new primary MLBCLs had prominent c-REL nuclear staining, and the MLBCL cell line exhibited high levels of NFkappaB binding activity. MLBCL cells expressing a superrepressor form of inhibitor of kappa B alpha signaling (IkappaB alpha) had a markedly higher rate of apoptosis, implicating constitutive NFkappaB activity in MLBCL cell survival. The transcriptional profiles of newly diagnosed primary MLBCLs and diffuse large B-cell lymphomas (DLBCLs) were then used to characterize the NFkappaB target gene signatures of MLBCL and specific DLBCL subtypes. MLBCLs expressed increased levels of NFkappaB targets that promote cell survival and favor antiapoptotic tumor necrosis factor alpha (TNFalpha) signaling. In contrast, activated B cell (ABC)-like DLBCLs had a more restricted, potentially developmentally regulated, NFkappaB target gene signature. Of interest, the newly characterized host response DLBCL subtype had a robust NFkappaB target gene signature that partially overlapped that of primary MLBCL. In this large series of primary MLBCLs and DLBCLs, NFkappaB activation was not associated with amplification of the cREL locus, suggesting alternative pathogenetic mechanisms.

Apoptosis↗
PubMed2006

Identification of a common gene signature for type II cytokine-associated myeloid cells elicited in vivo in different pathologic conditions.

Compared with type I cytokine-associated myeloid (M1) cells, the molecular repertoire and mechanisms underlying functional properties of type II cytokine-associated myeloid (M2) cells are poorly characterized. Moreover, most studies have been limited to in vitro-elicited M2 cells. Here, comparative gene expression profiling of M1 and M2 cells, elicited in murine models of parasitic infections and cancer, yielded a common signature for in vivo-induced M2 populations independent of disease model, mouse strain, and organ source of cells. Some of these genes, such as cadherin-1, selenoprotein P, platelet-activating factor acetylhydrolase, and prosaposin, had not been documented as associated with M2. Overall, the common signature genes provide a molecular basis for a number of documented or suggested properties of M2, including immunomodulation, down-regulation of inflammation, protection against oxidative damage, high capacity for phagocytosis, and tissue repair. Interestingly, several common M2 signature genes encode membrane-associated markers that could be useful for the identification and isolation of M2. Some of these genes were not induced by IL-4/IL-13 or IL-10 under various in vitro settings and thus were missed in approaches based on in vitro-activated cells, validating our choice of in vivo models for expression profiling of myeloid cells.

Animals↗
PubMed2006

Gene-expression signature of benign monoclonal gammopathy evident in multiple myeloma is linked to good prognosis.

Monoclonal gammopathy of undetermined significance (MGUS) can progress to multiple myeloma (MM). Although these diseases share many of the same genetic features, it is still unclear whether global gene-expression profiling might identify prior genomic signatures that distinguish them. Through significance analysis of microarrays, 52 genes involved in important pathways related to cancer were differentially expressed in the plasma cells of healthy subjects (normal plasma-cell [NPC]; n=22) and patients with stringently defined MGUS/smoldering MM (n=24) and symptomatic MM (n=351) (P<.001). Unsupervised hierarchical clustering of 351 patients with MM, 44 with MGUS (24+20), and 16 with MM from MGUS created 2 major cluster branches, one containing 82% of the MGUS patients and the other containing 28% of the MM patients, termed MGUS-like MM (MGUS-L MM). Using the same clustering approach on an independent cohort of 214 patients with MM, 27% were found to be MGUS-L. This molecular signature, despite its association with a lower incidence of complete remission (P=.006), was associated with low-risk clinical and molecular features and superior survival (P<.01). The MGUS-L signature was also seen in plasma cells from 15 of 20 patients surviving more than 10 years after autotransplantation. These data provide insight into the molecular mechanisms of plasma-cell dyscrasias.

Aged↗
PubMed2003

Identification of signature and primers specific to genus Pseudomonas using mismatched patterns of 16S rDNA sequences.

BACKGROUND: Pseudomonas, a soil bacterium, has been observed as a dominant genus that survives in different habitats with wide hostile conditions. We had a basic assumption that the species level variation in 16S rDNA sequences of a bacterial genus is mainly due to substitutions rather than insertion or deletion of bases. Keeping this in view, the aim was to identify a region of 16S rDNA sequence and within that focus on substitution prone stretches indicating species level variation and to derive patterns from these stretches that are specific to the genus. RESULTS: Repeating elements that are highly conserved across different species of Pseudomonas were considered as guiding markers to locate a region within the 16S gene. Four repeating patterns showing more than 80% consistency across fifty different species of Pseudomonas were identified. The sub-sequences between the repeating patterns yielded a continuous region of 495 bases. The sub-sequences after alignment and using Shanon's entropy measure yielded a consensus pattern. A stretch of 24 base positions in this region, showing maximum variations across the sampled sequences was focused for possible genus specific patterns. Nine patterns in this stretch showed nearly 70% specificity to the target genus. These patterns were further used to obtain a signature that is highly specific to Pseudomonas. The signature region was used to design PCR primers, which yielded a PCR product of 150 bp whose specificity was validated through a sample experiment. CONCLUSIONS: The developed approach was successfully applied to genus Pseudomonas. It could be tried in other bacterial genera to obtain respective signature patterns and thereby PCR primers, for their rapid tracking in the environmental samples.

Base Pair Mismatch↗
PubMed2005

Sequence signature analysis of chromosome identity in three Drosophila species.

BACKGROUND: All eukaryotic organisms need to distinguish each of their chromosomes. A few protein complexes have been described that recognise entire, specific chromosomes, for instance dosage compensation complexes and the recently discovered autosome-specific Painting of Fourth (POF) protein in Drosophila. However, no sequences have been found that are chromosome-specific and distributed over the entire length of the respective chromosome. Here, we present a new, unbiased, exhaustive computational method that was used to probe three Drosophila genomes for chromosome-specific sequences. RESULTS: By combining genome annotations and cytological data with multivariate statistics related to three Drosophila genomes we found sequence signatures that distinguish Muller's F-elements (chromosome 4 in D. melanogaster) from all other chromosomes in Drosophila that are not attributable to differences in nucleotide composition, simple sequence repeats or repeated elements. Based on these signatures we identified complex motifs that are strongly overrepresented in the F-elements and found indications that the D. melanogaster motif may be involved in POF-binding to the F-element. In addition, the X-chromosomes of D. melanogaster and D. yakuba can be distinguished from the other chromosomes, albeit to a lesser extent. Surprisingly, the conservation of the F-element sequence signatures extends not only between species separated by approximately 55 Myr, but also linearly along the sequenced part of the F-elements. CONCLUSION: Our results suggest that chromosome-distinguishing features are not exclusive to the sex chromosomes, but are also present on at least one autosome (the F-element) in Drosophila.

Animals↗
PubMed2006

Molecular signatures (unique proteins and conserved indels) that are specific for the epsilon proteobacteria (Campylobacterales).

BACKGROUND: The epsilon proteobacteria, which include many important human pathogens, are presently recognized solely on the basis of their branching in rRNA trees. No unique molecular or biochemical characteristics specific for this group are known. RESULTS: Comparative analyses of proteins in the genomes of Wolinella succinogenes DSM 1740 and Campylobacter jejuni RM1221 against all available sequences have identified a large number of proteins that are unique to various epsilon proteobacteria (Campylobacterales), but whose homologs are not detected in other organisms. Of these proteins, 49 are uniquely found in nearly all sequenced epsilon-proteobacteria (viz. Helicobacter pylori (26695 and J99), H. hepaticus, C. jejuni (NCTC 11168, RM1221, HB93-13, 84-25, CF93-6, 260.94, 11168 and 81-176), C. lari, C. coli, C. upsaliensis, C. fetus, W. succinogenes DSM 1740 and Thiomicrospira denitrificans ATCC 33889), 11 are unique for the Wolinella and Helicobacter species (i.e. Helicobacteraceae family) and many others are specific for either some or all of the species within the Campylobacter genus. The primary sequences of many of these proteins are highly conserved and provide novel resources for diagnostics and therapeutics. We also report four conserved indels (i.e. inserts or deletions) in widely distributed proteins (viz. B subunit of exinuclease ABC, phenylalanyl-tRNA synthetase, RNA polymerase beta '-subunit and FtsH protein) that are specific for either all epsilon proteobacteria or different subgroups. In addition, a rare genetic event that caused fusion of the genes for the largest subunits of RNA polymerase (rpoB and rpoC) in Wolinella and Helicobacter is also described. The inter-relationships amongst Campylobacterales as deduced from these molecular signatures are in accordance with the phylogenetic trees based on the 16S rRNA and concatenated sequences for nine conserved proteins. CONCLUSION: These molecular signatures provide novel tools for identifying and circumscribing species from the Campylobacterales order and its subgroups in molecular terms. Although sequence information for these signatures is presently limited to Campylobacterales species, it is likely that many of them will also be found in other epsilon proteobacteria. Functional studies on these proteins and conserved indels should reveal novel biochemical or physiological characteristics that are unique to these groups of epsilon proteobacteria.

Bacterial Proteins↗
PubMed2006

Surface-antigen expression profiling of B cell chronic lymphocytic leukemia: from the signature of specific disease subsets to the identification of markers with prognostic relevance.

Studies of gene expression profiling have been successfully used for the identification of molecules to be employed as potential prognosticators. In analogy with gene expression profiling, we have recently proposed a novel method to identify the immunophenotypic signature of B-cell chronic lymphocytic leukemia subsets with different prognosis, named surface-antigen expression profiling. According to this approach, surface marker expression data can be analysed by data mining tools identical to those employed in gene expression profiling studies, including unsupervised and supervised algorithms, with the aim of identifying the immunophenotypic signature of B-cell chronic lymphocytic leukemia subsets with different prognosis. Here we provide an overview of the overall strategy employed for the development of such an "outcome class-predictor" based on surface-antigen expression signatures. In addition, we will also discuss how to transfer the obtained information into the routine clinical practice by providing a flow-chart indicating how to select the most relevant antigens and build-up a prognostic scoring system by weighing each antigen according to its predictive power. Although referred to B-cell chronic lymphocytic leukemia, the methodology discussed here can be also useful in the study of diseases other than B-cell chronic lymphocytic leukemia, when the purpose is to identify novel prognostic determinants.

Journal Article↗
PubMed2004

Gene expression signature with independent prognostic significance in epithelial ovarian cancer.

PURPOSE: Currently available clinical and molecular prognostic factors provide an imperfect assessment of prognosis for patients with epithelial ovarian cancer (EOC). In this study, we investigated whether tumor transcription profiling could be used as a prognostic tool in this disease. METHODS: Tumor tissue from 68 patients was profiled with oligonucleotide microarrays. Samples were randomly split into training and validation sets. A three-step training procedure was used to discover a statistically significant Kaplan-Meier split in the training set. The resultant prognostic signature was then tested on an independent validation set for confirmation. RESULTS: In the training set, a 115-gene signature referred to as the Ovarian Cancer Prognostic Profile (OCPP) was identified. When applied to the validation set, the OCPP distinguished between patients with unfavorable and favorable overall survival (median, 30 months v not yet reached, respectively; log-rank P = .004). The signature maintained independent prognostic value in multivariate analysis, controlling for other known prognostic factors such as age, stage, grade, and debulking status. The hazard ratio for death in the unfavorable OCPP group was 4.8 (P = .021 by Cox proportional hazards analysis). CONCLUSION: The OCPP is an independent prognostic determinant of outcome in EOC. The use of gene profiling may ultimately permit identification of EOC patients appropriate for investigational treatment approaches, based on a low likelihood of achieving prolonged survival with standard first-line platinum-based therapy.

Adult↗
PubMed2006

Noise, clutter, and determinism in infrared spectral signatures under varying meteorological conditions.

Infrared remote detection of chemical and biological agents in a complex environment depends on the ability to recognize threat signatures and differentiate them from the signatures of innocuous materials. In this paper, we addressed the methods of producing the constraint spectra needed to ensure reliable operation in a meteorologically changing environment. We collected arrays of background spectra of ground, woods, and low-angle sky on an irregular basis over a period of a year. Based on the hypothesis that the concentration fluctuations of species in the sensor's field of view can be exploited to form signatures, the standard deviations of the array (the result is characteristic of all fluctuations) and the difference array (the result is characteristic of sensor fluctuations) were computed. Subtracting these two spectra and filtering the result produced a spectrum, which is a measure of the IR fluctuations in the scene. The resulting set of scene spectra were processed into aberrant noise, and deterministic groups by numerical filtering and statistical methods.

Journal Article↗
PubMed2006

Soft sweeps III: the signature of positive selection from recurrent mutation.

Polymorphism data can be used to identify loci at which a beneficial allele has recently gone to fixation, given that an accurate description of the signature of selection is available. In the classical model that is used, a favored allele derives from a single mutational origin. This ignores the fact that beneficial alleles can enter a population recurrently by mutation during the selective phase. In this study, we present a combination of analytical and simulation results to demonstrate the effect of adaptation from recurrent mutation on summary statistics for polymorphism data from a linked neutral locus. We also analyze the power of standard neutrality tests based on the frequency spectrum or on linkage disequilibrium (LD) under this scenario. For recurrent beneficial mutation at biologically realistic rates, we find substantial deviations from the classical pattern of a selective sweep from a single new mutation. Deviations from neutrality in the level of polymorphism and in the frequency spectrum are much less pronounced than in the classical sweep pattern. In contrast, for levels of LD, the signature is even stronger if recurrent beneficial mutation plays a role. We suggest a variant of existing LD tests that increases their power to detect this signature.

Alleles↗
PubMed2007

Use of massively parallel signature sequencing to study genes expressed during the plant defense response.

Massively parallel signature sequencing is a sequencing-based method that provides quantitative gene expression data for nearly all transcripts in a particular ribonucleic acid sample. Although the sequencing technology is practiced as a service by a California-based company, we have developed methods for the handling and analysis of these data. This chapter describes the steps involved in obtaining data from massively parallel signature sequencing, aligning the signatures to genomic sequence, identifying novel transcripts, and performing quantitative analyses of genes expressed under conditions such as disease treatments.

Arabidopsis↗
PubMed2004

Linkage disequilibrium as a signature of selective sweeps.

The hitchhiking effect of a beneficial mutation, or a selective sweep, generates a unique distribution of allele frequencies and spatial distribution of polymorphic sites. A composite-likelihood test was previously designed to detect these signatures of a selective sweep, solely on the basis of the spatial distribution and marginal allele frequencies of polymorphisms. As an excess of linkage disequilibrium (LD) is also known to be a strong signature of a selective sweep, we investigate how much statistical power is increased by the inclusion of information regarding LD. The expected pattern of LD is predicted by a genealogical approach. Both theory and simulation suggest that strong LD is generated in narrow regions at both sides of the location of beneficial mutation. However, a lack of LD is expected across the two sides. We explore various ways to detect this signature of selective sweeps by statistical tests. A new composite-likelihood method is proposed to incorporate information regarding LD. This method enables us to detect selective sweeps and estimate the parameters of the selection model better than the previous composite-likelihood method that does not take LD into account. However, the improvement made by including LD is rather small, suggesting that most of the relevant information regarding selective sweeps is captured by the spatial distribution and marginal allele frequencies of polymorphisms.

Computer Simulation↗
PubMed1978

A preliminary study in the detection of cardiac disorders via phase-invariant signature algorithm of ECG.

The present paper presents a simple and unambiguous computer-assisted method for the detection of cardiac disorders by processing the electrocardiogram. A new technique "Phase Invariant Signature Algorithm (PISA)", has been described, which is useful in the detection of cardiac abnormalities by investigating certain statistical properties of the measured waveform of ECG in a "phase-locked" fashion. This method of detection of abnormalities in the heart was used in the changes in the hypoxic action potential and in the ECG due to ionic changes and ischemia in the heart of cats and dogs. The signature of the normal ECG or action potential was straight-line. Any change in the waveform of ECG or action potential was detected as spikes in the signature. This method of detection of cardiac abnormalities does not require a priori reference to any standard ECG. The results indicate that this new method is capable of detecting cardiac disorders at an early stage and hence a higher sensitivity than the presently available type of ECG analysis. This method is in the developmental stage and further studies are being carried out.

Animals↗
PubMed2026

TFPI-high myofibroblast states and a meta-program-related five-gene prognostic signature in breast cancer.

Intratumoral heterogeneity and tumor-microenvironment interactions limit prognostic stratification in breast cancer, but the prognostic relevance and cellular context of recurrent transcriptional meta-programs remain unclear. We aimed to derive a meta-program-related prognostic signature and characterize its component transcripts at single-cell resolution. Six paired institutional tumors and adjacent non-tumor tissues served as a proof-of-concept comparison. Univariable Cox screening and least absolute shrinkage and selection operator Cox regression were used to derive a five-gene score from a prespecified meta-program-related candidate set in The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) training cohort; the score was tested internally and assessed in GSE20685 using fixed coefficients and cohort-specific median cutoffs. GSE161529 single-cell transcriptomic data were used to map signature transcripts across 136,526 quality-controlled cells, while donor-aware pseudobulk analysis compared upper- and lower-quartile TFPI expression states in annotated myofibroblasts. The score comprised TCN1, FOXJ1, PIGR, SLAIN1, and TFPI and was associated with overall survival in the training, testing, and external cohorts, with concordance indices of 0.782, 0.756, and 0.721, respectively. TFPI transcripts were detected across endothelial, fibroblast, and myofibroblast compartments. TFPI-high myofibroblasts showed transcriptional enrichment of extracellular matrix and collagen fibril organization, transforming growth factor beta signaling, epithelial-mesenchymal transition, and myogenesis, together with lower oxidative phosphorylation and fatty acid metabolism programs. In bulk TCGA-BRCA tissue, TFPI expression correlated positively with stromal (r&#xa0;= 0.48), immune (r&#xa0;= 0.25), and composite microenvironment scores (r&#xa0;= 0.40; all p&#xa0;< 0.001). These findings identify a hypothesis-generating five-gene bulk-tissue prognostic signature and an expression-associated TFPI-high myofibroblast state but do not establish a discrete lineage, the cellular source of bulk TFPI, a TFPI-dependent mechanism, or clinical utility. Independent prospective cohorts, spatial and protein-level validation, and functional perturbation studies are required.

Journal Article↗
PubMed2026

SERPINE1-centric inflammatory signature associates with treatment resistance and survival in laryngeal squamous cell carcinoma.

BACKGROUND: Laryngeal squamous cell carcinoma (LSCC) prognosis remains poor despite treatment advances. More accurate prognostic assessment models can help guide individualized treatment and improve prognosis. Chronic inflammation contributes to tumorigenesis, yet inflammatory response-related genes (IRGs) in LSCC prognosis are underexplored. This study aimed to construct an IRG prognostic signature for LSCC and further dissect core IRG-mediated mechanisms of immune escape and chemoresistance. METHODS: Transcriptional profiles and clinical data from LSCC patients were retrieved from The Cancer Genome Atlas (TCGA). IRGs were sourced from Gene Set Enrichment Analysis (GSEA) hallmark gene set. We identified differentially expressed IRGs linked to survival outcomes in LSCC. Key IRGs were subsequently selected using least absolute shrinkage and selection operator (LASSO) Cox regression analysis to establish an inflammatory risk score model. This model underwent internal validation within the TCGA cohort and external validation using independent Gene Expression Omnibus (GEO) datasets. We further assessed the model's association with the tumor immune microenvironment and the impact of IRGs on chemotherapy response. Finally, the functional roles of interested signature IRG were experimentally validated in LSCC cell lines. RESULTS: Four significant IRGs (AQP9, ITGA5, LCK, SERPINE1) were identified to build the risk score model. The model stratified LSCC patients into distinct prognostic groups: TCGA cohort: 5-year area under the curve (AUC) =0.836, P<0.001; GSE25727 cohort: 5-year AUC =0.706, P=0.02; GSE27020 cohort: 5-year AUC =0.798, P<0.01. Multivariate analysis confirmed the risk score as an independent prognostic factor (P<0.05). High-risk patients showed reduced immune cell infiltration (CD8+ T cells, dendritic cells) and suppressed immune pathways. Multi-algorithm immune analysis further revealed defective antigen presentation and reduced anti-tumor immune infiltration in high-risk LSCC, promoting tumor immune escape. GSEA/Gene Ontology (GO) enrichment combined with drug sensitivity prediction further revealed that high-risk tumors activate invasive signaling and acquire broad chemoresistance alongside impaired anti-tumor immunity. SERPINE1 might be associated with chemotherapy resistance and exhibited the highest alteration frequency (predominantly amplification) and overexpression in LSCC tissues. Its knockdown significantly suppressed proliferation, migration, invasion and chemoresistance in LSCC cells. Immunohistochemistry (IHC) confirmed tumor SERPINE1 overexpression (P=0.002 vs. normal tissues), correlating with poor survival (P<0.001). CONCLUSIONS: The 4-IRG risk signature is a reliable prognostic indicator reflecting immune dysfunction in LSCC. SERPINE1 is validated as a therapeutic target and biomarker, enriching our understanding of gene regulation dynamics in LSCC.

Laryngeal cancer↗