Proteogenomics of non-small cell lung cancer reveals molecular subtypes associated with specific therapeutic targets and immune evasion mechanisms

Fibrinogen-like 1: A hepatokine linking liver physiology to hematology

A recent study identified the critical contribution of the hepatokine FGL1 to the regulation of iron metabolism during the recovery from anemia. FGL1 is secreted by hepatocytes in response to hypoxia to sequester BMP ligands and repress the transcription of the iron-regulatory hormone hepcidin. This process ensures the proper supply of iron to the bone marrow for new red blood cell synthesis and the restoration of physiological oxygen levels. FGL1 may therefore contribute to the recovery from common anemias and cause iron overload in chronic anemias with ineffective erythropoiesis, such as ß-thalassemia, dyserythropoietic anemia, and myelodysplastic syndromes. However, FGL1 has also been described as a regulator of hepatocyte proliferation, glucose homeostasis, and insulin signaling, as well as a mediator of liver steatosis and immune evasion. Chronic exposure to elevated levels of FGL1 during anemia may therefore have systemic metabolic effects besides iron regulation and erythropoiesis. Here, we are providing an overview of the proposed functions of FGL1 in physiology and pathophysiology.

Cancer Core Europe: Leveraging Institutional Synergies to Advance Oncology Research and Care Globally

Cancer Core Europe brings together the expertise, resources, and interests of seven leading cancer institutes committed to leveraging collective innovation and collaboration in precision oncology. Through targeted efforts addressing key medical challenges in cancer and partnerships with multiple stakeholders, the consortium seeks to advance cancer research and enhance equitable patient care.

Deciphering the tumor immune microenvironment from a multidimensional omics perspective: insight into next-generation CAR-T cell immunotherapy and beyond

Tumor immune microenvironment (TIME) consists of intra-tumor immunological components and plays a significant role in tumor initiation, progression, metastasis, and response to therapy. Chimeric antigen receptor (CAR)-T cell immunotherapy has revolutionized the cancer treatment paradigm. Although CAR-T cell immunotherapy has emerged as a successful treatment for hematologic malignancies, it remains a conundrum for solid tumors. The heterogeneity of TIME is responsible for poor outcomes in CAR-T cell immunotherapy against solid tumors. The advancement of highly sophisticated technology enhances our exploration in TIME from a multi-omics perspective. In the era of machine learning, multi-omics studies could reveal the characteristics of TIME and its immune resistance mechanism. Therefore, the clinical efficacy of CAR-T cell immunotherapy in solid tumors could be further improved with strategies that target unfavorable conditions in TIME. Herein, this review seeks to investigate the factors influencing TIME formation and propose strategies for improving the effectiveness of CAR-T cell immunotherapy through a multi-omics perspective, with the ultimate goal of developing personalized therapeutic approaches.

Data-independent acquisition: A milestone and prospect in clinical mass spectrometry-based proteomics

Data-independent acquisition (DIA) has revolutionized the field of mass spectrometry (MS)-based proteomics over the past few years. DIA stands out for its ability to systematically sample all peptides in a given mass-to-charge range, allowing an unbiased acquisition of proteomics data. This greatly mitigates the issue of missing values and significantly enhances quantitative accuracy, precision, and reproducibility compared to many traditional methods. This review focuses on the critical role of DIA analysis software tools, primarily focusing on their capabilities and the challenges they address in proteomic research. Advances in MS technology, such as trapped ion mobility spectrometry, or high field asymmetric waveform ion mobility spectrometry require sophisticated analysis software capable of handling the increased data complexity and exploiting the full potential of DIA. We identify and critically evaluate leading software tools in the DIA landscape, discussing their unique features, and the reliability of their quantitative and qualitative outputs. We present the biological and clinical relevance of DIA-MS and discuss crucial publications that paved the way for in-depth proteomic characterization in patient-derived specimens. Furthermore, we provide a perspective on emerging trends in clinical applications and present upcoming challenges including standardization and certification of MS-based acquisition strategies in molecular diagnostics. While we emphasize the need for continuous development of software tools to keep pace with evolving technologies, we advise researchers against uncritically accepting the results from DIA software tools. Each tool may have its own biases, and some may not be as sensitive or reliable as others. Our overarching recommendation for both researchers and clinicians is to employ multiple DIA analysis tools, utilizing orthogonal analysis approaches to enhance the robustness and reliability of their findings.

Molecular subtypes of neuroendocrine carcinomas: A cross-tissue classification framework based on five transcriptional regulators

Neuroendocrine carcinomas (NECs) are extremely lethal malignancies that can arise at almost any anatomic site. Characterization of NECs is hindered by their rarity and significant inter- and intra-tissue heterogeneity. Herein, through an integrative analysis of over 1,000 NECs originating from 31 various tissues, we reveal their tissue-independent convergence and further unveil molecular divergence driven by distinct transcriptional regulators. Pan-tissue NECs are therefore categorized into five intrinsic subtypes defined by ASCL1, NEUROD1, HNF4A, POU2F3, and YAP1. A comprehensive portrait of these subtypes is depicted, highlighting subtype-specific transcriptional programs, genomic alterations, evolution trajectories, therapeutic vulnerabilities, and clinicopathological presentations. Notably, the newly discovered HNF4A-dominated subtype-H exhibits a gastrointestinal-like signature, wild-type RB1, unique neuroendocrine differentiation, poor chemotherapeutic response, and prevalent large-cell morphology. The proposal of uniform classification paradigm illuminates transcriptional basis of NEC heterogeneity and bridges the gap across different lineages and cytomorphological variants, in which context-dependent prevalence of subtypes underlies their phenotypic disparities.

High-throughput molecular assays for inclusion in personalised oncology trials - State-of-the-art and beyond

In the last decades, the development of high-throughput molecular assays has revolutionised cancer diagnostics, paving the way for the concept of personalised cancer medicine. This progress has been driven by the introduction of such technologies through biomarker-driven oncology trials. In this review, strengths and limitations of various state-of-the-art sequencing technologies, including gene panel sequencing (DNA and RNA), whole-exome/whole-genome sequencing and whole-transcriptome sequencing, are explored, focusing on their ability to identify clinically relevant biomarkers with diagnostic, prognostic and/or predictive impact. This includes the need to assess complex biomarkers, for example microsatellite instability, tumour mutation burden and homologous recombination deficiency, to identify patients suitable for specific therapies, including immunotherapy. Furthermore, the crucial role of biomarker analysis and multidisciplinary molecular tumour boards in selecting patients for trial inclusion is discussed in relation to various trial concepts, including drug repurposing. Recognising that today's exploratory techniques will evolve into tomorrow's routine diagnostics and clinical study inclusion assays, the importance of emerging technologies for multimodal diagnostics, such as proteomics and in vivo drug sensitivity testing, is also discussed. In addition, key regulatory aspects and the importance of patient engagement in all phases of a clinical trial are described. Finally, we propose a set of recommendations for consideration when planning a new precision cancer medicine trial.

HERC5 downregulation in non-small cell lung cancer is associated with altered energy metabolism and metastasis

BACKGROUND

Metastasis is the leading cause of cancer-related death in non-small cell lung cancer (NSCLC) patients. We previously showed that low HERC5 expression predicts early tumor dissemination and a dismal prognosis in NSCLC patients. Here, we performed functional studies to unravel the mechanism underlying the "metastasis-suppressor" effect of HERC5, with a focus on mitochondrial metabolism pathways.

METHODS

We assessed cell proliferation, colony formation potential, anchorage-independent growth, migration, and wound healing in NSCLC cell line models with HERC5 overexpression (OE) or knockout (KO). To study early tumor cell dissemination, we used these cell line models in zebrafish experiments and performed intracardial injections in nude mice. Mass spectrometry (MS) was used to analyze protein changes in whole-cell extracts. Furthermore, electron microscopy (EM) imaging, cellular respiration, glycolytic activity, and lactate production were used to investigate the relationships with mitochondrial energy metabolism pathways.

RESULTS

Using different in vitro NSCLC cell line models, we showed that NSCLC cells with low HERC5 expression had increased malignant and invasive properties. Furthermore, two different in vivo models in zebrafish and a xenograft mouse model showed increased dissemination and metastasis formation (in particular in the brain). Functional enrichment clustering of MS data revealed an increase in mitochondrial proteins in vitro when HERC5 levels were high. Loss of HERC5 leads to an increased Warburg effect, leading to improved adaptation and survival under prolonged inhibition of oxidative phosphorylation.

CONCLUSIONS

Taken together, these results indicate that low HERC5 expression increases the metastatic potential of NSCLC in vitro and in vivo. Furthermore, HERC5-induced proteomic changes influence mitochondrial pathways, ultimately leading to alterations in energy metabolism and demonstrating its role as a new potential metastasis suppressor gene.

Germline USP36 Mutation Confers Resistance to EGFR-TKIs by Upregulating MLLT3 Expression in Patients with Non-Small Cell Lung Cancer

PURPOSE

Although somatic mutations were explored in depth, limited biomarkers were found to predict the resistance of EGFR tyrosine kinase inhibitors (EGFR-TKI). Previous studies reported N6-methyladenosine (m6A) levels regulated response of EGFR-TKIs; whether the germline variants located in m6A sites affected resistance of EGFR-TKIs is still unknown.

EXPERIMENTAL DESIGN

Patients with non-small cell lung cancer (NSCLC) with EGFR-activating mutation were enrolled to investigate predictors for response of EGFR-TKIs using a genome-wide-variant-m6A analysis. Bioinformatics analysis and series of molecular biology assays were used to uncover the underlying mechanism.

RESULTS

We identified the germline mutation USP36 rs3744797 (C > A, K814N) was associated with survival of patients with NSCLC treated with gefitinib [median progression-free survival (PFS): CC vs. CA, 16.30 vs. 10.50 months, P < 0.0001, HR = 2.45] and erlotinib (median PFS: CC vs. CA, 14.13 vs. 9.47 months, P = 0.041, HR = 2.63). Functionally, the C > A change significantly upregulated USP36 expression by reducing its m6A level. Meanwhile, rs3744797_A (USP36 MUT) was found to facilitate proliferation, migration, and resistance to EGFR-TKIs via upregulating MLLT3 expression in vitro and in vivo. More importantly, MLLT3 and USP36 levels are tightly correlated in patients with NSCLC, which were associated with prognosis of patients. Mechanistically, USP36 MUT stabilized MLLT3 by deubiquitinating MLLT3 in nucleoli and consequently activating its downstream signaling (HIF1α and Snai). Furthermore, inhibition of MLLT3 alleviated USP36 variant-induced EGFR-TKIs resistance in EGFR-mutant NSCLC.

CONCLUSIONS

These findings characterized rs3744797 as an oncogenic variant in mediating EGFR-TKI resistance and tumor aggressiveness through deubiquitinating MLLT3, highlighting the variant as a predictive biomarker for EGFR-TKI response in NSCLC.

Current and emerging sequencing-based tools for precision cancer medicine

Current precision cancer medicine is dependent on the analyses of a plethora of clinically relevant genomic aberrations. During the last decade, next-generation sequencing (NGS) has gradually replaced most other methods for precision cancer diagnostics, spanning from targeted tumor-informed assays and gene panel sequencing to global whole-genome and whole-transcriptome sequencing analyses. The shift has been impelled by a clinical need to assess an increasing number of genomic alterations with diagnostic, prognostic and predictive impact, including more complex biomarkers (e.g. microsatellite instability, MSI, and homologous recombination deficiency, HRD), driven by the parallel development of novel targeted therapies and enabled by the rapid reduction in sequencing costs. This review focuses on these sequencing-based methods, puts their emergence in a historic perspective, highlights their clinical utility in diagnostics and decision-making in pediatric and adult cancer, as well as raises challenges for their clinical implementation. Finally, the importance of applying sensitive tools for longitudinal monitoring of treatment response and detection of measurable residual disease, as well as future avenues in the rapidly evolving field of sequencing-based methods are discussed.

The hepatokine FGL1 regulates hepcidin and iron metabolism during anemia in mice by antagonizing BMP signaling

ABSTRACT

As a functional component of erythrocyte hemoglobin, iron is essential for oxygen delivery to all tissues in the body. The liver-derived peptide hepcidin is the master regulator of iron homeostasis. During anemia, the erythroid hormone erythroferrone regulates hepcidin synthesis to ensure the adequate supply of iron to the bone marrow for red blood cell production. However, mounting evidence suggested that another factor may exert a similar function. We identified the hepatokine fibrinogen-like 1 (FGL1) as a previously undescribed suppressor of hepcidin that is induced in the liver in response to hypoxia during the recovery from anemia, and in thalassemic mice. We demonstrated that FGL1 is a potent suppressor of hepcidin in vitro and in vivo. Deletion of Fgl1 in mice results in higher hepcidin levels at baseline and after bleeding. FGL1 exerts its activity by directly binding to bone morphogenetic protein 6 (BMP6), thereby inhibiting the canonical BMP-SMAD signaling cascade that controls hepcidin transcription.

METTL3 drives NSCLC metastasis by enhancing CYP19A1 translation and oestrogen synthesis

BACKGROUND

METTL3 plays a significant role as a catalytic enzyme in mediating N6-methyladenosine (m6A) modification, and its importance in tumour progression has been extensively studied in recent years. However, the precise involvement of METTL3 in the regulation of translation in non-small cell lung cancer (NSCLC) remains unclear.

RESULTS

Here we discovered by clinical investigation that METTL3 expression is correlated with NSCLC metastasis. Ablation of METTL3 in NSCLC cells inhibits invasion and metastasis in vitro and in vivo. Subsequently, through translatomics data mining and experimental validation, we demonstrated that METTL3 enhances the translation of aromatase (CYP19A1), a key enzyme in oestrogen synthesis, thereby promoting oestrogen production and mediating the invasion and metastasis of NSCLC. Mechanistically, METTL3 interacts with translation initiation factors and binds to CYP19A1 mRNA, thus enhancing the translation efficiency of CYP19A1 in an m6A-dependent manner. Pharmacological inhibition of METTL3 enzymatic activity or translation initiation factor eIF4E abolishes CYP19A1 protein synthesis.

CONCLUSIONS

Our findings indicate the crucial role of METTL3-mediated translation regulation in NSCLC and reveal the significance of METTL3/eIF4E/CYP19A1 signaling as a promising therapeutic target for anti-metastatic strategies against NSCLC.

Inhalable point-of-care urinary diagnostic platform

Although low-dose computed tomography screening improves lung cancer survival in at-risk groups, inequality remains in lung cancer diagnosis due to limited access to and high costs of medical imaging infrastructure. We designed a needleless and imaging-free platform, termed PATROL (point-of-care aerosolizable nanosensors with tumor-responsive oligonucleotide barcodes), to reduce resource disparities for early detection of lung cancer. PATROL formulates a set of DNA-barcoded, activity-based nanosensors (ABNs) into an inhalable format. Lung cancer-associated proteases selectively cleave the ABNs, releasing synthetic DNA reporters that are eventually excreted via the urine. The urinary signatures of barcoded nanosensors are quantified within 20 min at room temperature using a multiplexable paper-based lateral flow assay. PATROL detects early-stage tumors in an autochthonous lung adenocarcinoma mouse model with high sensitivity and specificity. Tailoring the library of ABNs may enable not only the modular PATROL platform to lower the resource threshold for lung cancer early detection tools but also the rapid detection of chronic pulmonary disorders and infections.

CD47: The Next Frontier in Immune Checkpoint Blockade for Non-Small Cell Lung Cancer

The success of PD-1/PD-L1-targeted therapy in lung cancer has resulted in great enthusiasm for additional immunotherapies in development to elicit similar survival benefits, particularly in patients who do not respond to or are ineligible for PD-1 blockade. CD47 is an immunosuppressive molecule that binds SIRPα on antigen-presenting cells to regulate an innate immune checkpoint that blocks phagocytosis and subsequent activation of adaptive tumor immunity. In lung cancer, CD47 expression is associated with poor survival and tumors with EGFR mutations, which do not typically respond to PD-1 blockade. Given its prognostic relevance, its role in facilitating immune escape, and the number of agents currently in clinical development, CD47 blockade represents a promising next-generation immunotherapy for lung cancer. In this review, we briefly summarize how tumors disrupt the cancer immunity cycle to facilitate immune evasion and their exploitation of immune checkpoints like the CD47-SIRPα axis. We also discuss approved immune checkpoint inhibitors and strategies for targeting CD47 that are currently being investigated. Finally, we review the literature supporting CD47 as a promising immunotherapeutic target in lung cancer and offer our perspective on key obstacles that must be overcome to establish CD47 blockade as the next standard of care for lung cancer therapy.

The liver microenvironment orchestrates FGL1-mediated immune escape and progression of metastatic colorectal cancer

Colorectal cancer (CRC) patients with liver metastases usually obtain less benefit from immunotherapy, and the underlying mechanisms remain understudied. Here, we identify that fibrinogen-like protein 1 (FGL1), secreted from cancer cells and hepatocytes, facilitates the progression of CRC in an intraportal injection model by reducing the infiltration of T cells. Mechanistically, tumor-associated macrophages (TAMs) activate NF-ĸB by secreting TNFα/IL-1β in the liver microenvironment and transcriptionally upregulate OTU deubiquitinase 1 (OTUD1) expression, which enhances FGL1 stability via deubiquitination. Disrupting the TAM-OTUD1-FGL1 axis inhibits metastatic tumor progression and synergizes with immune checkpoint blockade (ICB) therapy. Clinically, high plasma FGL1 levels predict poor outcomes and reduced ICB therapy benefits. Benzethonium chloride, an FDA-approved antiseptics, curbs FGL1 secretion, thereby inhibiting liver metastatic tumor growth. Overall, this study uncovers the critical roles and posttranslational regulatory mechanism of FGL1 in promoting metastatic tumor progression, highlighting the TAM-OTUD1-FGL1 axis as a potential target for cancer immunotherapy.

FBXL12 degrades FANCD2 to regulate replication recovery and promote cancer cell survival under conditions of replication stress

Fanconi anemia (FA) signaling, a key genomic maintenance pathway, is activated in response to replication stress. Here, we report that phosphorylation of the pivotal pathway protein FANCD2 by CHK1 triggers its FBXL12-dependent proteasomal degradation, facilitating FANCD2 clearance at stalled replication forks. This promotes efficient DNA replication under conditions of CYCLIN E- and drug-induced replication stress. Reconstituting FANCD2-deficient fibroblasts with phosphodegron mutants failed to re-establish fork progression. In the absence of FBXL12, FANCD2 becomes trapped on chromatin, leading to replication stress and excessive DNA damage. In human cancers, FBXL12, CYCLIN E, and FA signaling are positively correlated, and FBXL12 upregulation is linked to reduced survival in patients with high CYCLIN E-expressing breast tumors. Finally, depletion of FBXL12 exacerbated oncogene-induced replication stress and sensitized cancer cells to drug-induced replication stress by WEE1 inhibition. Collectively, our results indicate that FBXL12 constitutes a vulnerability and a potential therapeutic target in CYCLIN E-overexpressing cancers.

Proteogenomics in Cancer: Then and Now

For years, the paths of sequencing technologies and mass spectrometry have occurred in isolation, with each developing its own unique culture and expertise. These two technologies are crucial for inspecting complementary aspects of the molecular phenotype across the central dogma. Integrative multiomics strives to bridge the analysis gap among different fields to complete more comprehensive mechanisms of life events and diseases. Proteogenomics is one integrated multiomics field. Here in this review, we mainly summarize and discuss three aspects: workflow of proteogenomics, proteogenomics applications in cancer research, and the SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis of proteogenomics in cancer research. In conclusion, proteogenomics has a promising future as it clarifies the functional consequences of many unannotated genomic abnormalities or noncanonical variants and identifies driver genes and novel therapeutic targets across cancers, which would substantially accelerate the development of precision oncology.

Precision cancer medicine: Concepts, current practice, and future developments

Precision cancer medicine is a multidisciplinary team effort that requires involvement and commitment of many stakeholders including the society at large. Building on the success of significant advances in precision therapy for oncological patients over the last two decades, future developments will be significantly shaped by improvements in scalable molecular diagnostics in which increasingly complex multilayered datasets require transformation into clinically useful information guiding patient management at fast turnaround times. Adaptive profiling strategies involving tissue- and liquid-based testing that account for the immense plasticity of cancer during the patient's journey and also include early detection approaches are already finding their way into clinical routine and will become paramount. A second major driver is the development of smart clinical trials and trial concepts which, complemented by real-world evidence, rapidly broaden the spectrum of therapeutic options. Tight coordination with regulatory agencies and health technology assessment bodies is crucial in this context. Multicentric networks operating nationally and internationally are key in implementing precision oncology in clinical practice and support developing and improving the ecosystem and framework needed to turn invocation into benefits for patients. The review provides an overview of the diagnostic tools, innovative clinical studies, and collaborative efforts needed to realize precision cancer medicine.

TIMP1 is an early biomarker for detection and prognosis of lung cancer

BACKGROUND

Lung cancer remains the major cause of cancer-related deaths worldwide. Early stages of lung cancer are characterized by long asymptomatic periods that are ineffectively identified with the current screening programs. This deficiency represents a lost opportunity to improve the overall survival of patients. Serum biomarkers are among the most effective strategies for cancer screening and follow up.

METHODS

Using bead-based multiplexing assays we screened plasma and tumours of the KrasG12D/+; Lkb1f/f (KL) mouse model of lung cancer for cytokines that could be used as biomarkers. We identified tissue inhibitor of metalloproteinase 1 (TIMP1) as an early biomarker and validated this finding in the plasma of lung cancer patients. We used immunohistochemistry (IHC), previously published single-cell RNA-seq and bulk RNA-seq data to assess the source and expression of TIMP1in the tumour. The prognostic value of TIMP1 was assessed using publicly available human proteomic and transcriptomic databases.

RESULTS

We found that TIMP1 is a tumour-secreted protein with high sensitivity and specificity for aggressive cancer, even at early stages in mice. We showed that TIMP1 levels in the tumour and serum correlate with tumour burden and worse survival in mice. We validated this finding using clinical samples from our institution and publicly available human proteomic and transcriptomic databases. These data support the finding that high tumour expression of TIMP1 correlates with an unfavorable prognosis in lung cancer patients.

CONCLUSION

TIMP1 is a suitable biomarker for lung cancer detection.

A CD276-Targeted Antibody-Drug Conjugate to Treat Non-Small Lung Cancer (NSCLC)

Non-small cell lung cancer (NSCLC) patients, accounting for approximately 85% of lung cancer cases, are usually diagnosed in advanced stages. Traditional surgical resection and radiotherapy have very limited clinical benefits. The objective of this study was to develop and evaluate a targeted therapy, antibody-drug conjugate (ADC), for NSCLC treatment. Specifically, the CD276 receptor was evaluated and confirmed as an ideal surface target of NSCLC in the immunohistochemistry (IHC) staining of seventy-three patient tumor microarrays and western blotting analysis of eight cell lines. Our anti-CD276 monoclonal antibody (mAb) with cross-activity to both human and mouse receptors showed high surface binding, effective drug delivery and tumor-specific targeting in flow cytometry, confocal microscopy, and in vivo imaging system analysis. The ADC constructed with our CD276 mAb and payload monomethyl auristatin F (MMAF) showed high anti-NSCLC cytotoxicity to multiple lines and effective anti-tumor efficacy in both immunocompromised and immunocompetent NSCLC xenograft mouse models. The brief mechanism study revealed the integration of cell proliferation inhibition and immune cell reactivation in tumor microenvironments. The toxicity study did not detect off-target immune toxicity or peripheral toxicity. Altogether, this study suggested that anti-CD276 ADC could be a promising candidate for NSCLC treatment.

Integrative splicing-quantitative-trait-locus analysis reveals risk loci for non-small-cell lung cancer

Splicing quantitative trait loci (sQTLs) have been demonstrated to contribute to disease etiology by affecting alternative splicing. However, the role of sQTLs in the development of non-small-cell lung cancer (NSCLC) remains unknown. Thus, we performed a genome-wide sQTL study to identify genetic variants that affect alternative splicing in lung tissues from 116 individuals of Chinese ancestry, which resulted in the identification of 1,385 sQTL-harboring genes (sGenes) containing 378,210 significant variant-intron pairs. A comprehensive characterization of these sQTLs showed that they were enriched in actively transcribed regions, genetic regulatory elements, and splicing-factor-binding sites. Moreover, sQTLs were largely distinct from expression quantitative trait loci (eQTLs) and showed significant enrichment in potential risk loci of NSCLC. We also integrated sQTLs into NSCLC GWAS datasets (13,327 affected individuals and 13,328 control individuals) by using splice-transcriptome-wide association study (spTWAS) and identified alternative splicing events in 19 genes that were significantly associated with NSCLC risk. By using functional annotation and experiments, we confirmed an sQTL variant, rs35861926, that reduced the risk of lung adenocarcinoma (rs35861926-T, OR = 0.88, 95% confidence interval [CI]: 0.82-0.93, p = 1.87 × 10-5) by promoting FARP1 exon 20 skipping to downregulate the expression level of the long transcript FARP1-011. Transcript FARP1-011 promoted the migration and proliferation of lung adenocarcinoma cells. Overall, our study provided informative lung sQTL resources and insights into the molecular mechanisms linking sQTL variants to NSCLC risk.

Proteogenomic data and resources for pan-cancer analysis

The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) investigates tumors from a proteogenomic perspective, creating rich multi-omics datasets connecting genomic aberrations to cancer phenotypes. To facilitate pan-cancer investigations, we have generated harmonized genomic, transcriptomic, proteomic, and clinical data for >1000 tumors in 10 cohorts to create a cohesive and powerful dataset for scientific discovery. We outline efforts by the CPTAC pan-cancer working group in data harmonization, data dissemination, and computational resources for aiding biological discoveries. We also discuss challenges for multi-omics data integration and analysis, specifically the unique challenges of working with both nucleotide sequencing and mass spectrometry proteomics data.

Spatially Resolved Proteomic and Transcriptomic Profiling of Anaplastic Lymphoma Kinase-Rearranged Pulmonary Adenocarcinomas Reveals Key Players in Inter- and Intratumoral Heterogeneity

Pulmonary adenocarcinomas (pADCs) with an ALK rearrangement are a rare cancer subtype, necessitating comprehensive molecular investigations to unravel their heterogeneity and improve therapeutic strategies. In this pilot study, we employed spatial transcriptomic (NanoString GeoMx) and proteomic profiling to investigate seven treatment-naïve pADCs with an ALK rearrangement. On each FFPE tumor slide, 12 smaller and 2-6 larger histopathologically annotated regions were selected for transcriptomic and proteomic analysis, respectively. The correlation between proteomics and transcriptomics was modest (average Pearson's r = 0.43 at the gene level). Intertumoral heterogeneity was more pronounced than intratumoral heterogeneity, and normal adjacent tissue exhibited distinct molecular characteristics. We identified potential markers and dysregulated pathways associated with tumors, with a varying extent of immune infiltration, as well as with mucin and stroma content. Notably, some markers appeared to be specific to the ALK-driven subset of pADCs. Our data showed that within tumors, elements of the extracellular matrix, including FN1, exhibited substantial variability. Additionally, we mapped the co-localization patterns of tumor microenvironment elements. This study represents the first spatially resolved profiling of ALK-driven pADCs at both the gene and protein expression levels. Our findings may contribute to a better understanding of this cancer type prior to treatment with ALK inhibitors.

Proteomic analysis reveals microvesicles containing NAMPT as mediators of radioresistance in glioma

Tumor-initiating cells contained within the aggressive brain tumor glioma (glioma stem cells, GSCs) promote radioresistance and disease recurrence. However, mechanisms of resistance are not well understood. Herein, we show that the proteome-level regulation occurring upon radiation treatment of several patient-derived GSC lines predicts their resistance status, whereas glioma transcriptional subtypes do not. We identify a mechanism of radioresistance mediated by the transfer of the metabolic enzyme NAMPT to radiosensitive cells through microvesicles (NAMPT-high MVs) shed by resistant GSCs. NAMPT-high MVs rescue the proliferation of radiosensitive GSCs and fibroblasts upon irradiation, and upon treatment with a radiomimetic drug or low serum, and increase intracellular NAD(H) levels. Finally, we show that the presence of NAMPT within the MVs and its enzymatic activity in recipient cells are necessary to mediate these effects. Collectively, we demonstrate that the proteome of GSCs provides unique information as it predicts the ability of glioma to resist radiation treatment. Furthermore, we establish NAMPT transfer via MVs as a mechanism for rescuing the proliferation of radiosensitive cells upon irradiation.

Genomic mapping of metastatic organotropism in lung adenocarcinoma

We analyzed 2,532 lung adenocarcinomas (LUAD) to identify the clinicopathological and genomic features associated with metastasis, metastatic burden, organotropism, and metastasis-free survival. Patients who develop metastasis are younger and male, with primary tumors enriched in micropapillary or solid histological subtypes and with a higher mutational burden, chromosomal instability, and fraction of genome doublings. Inactivation of TP53, SMARCA4, and CDKN2A are correlated with a site-specific shorter time to metastasis. The APOBEC mutational signature is more prevalent among metastases, particularly liver lesions. Analyses of matched specimens show that oncogenic and actionable alterations are frequently shared between primary tumors and metastases, whereas copy number alterations of unknown significance are more often private to metastases. Only 4% of metastases harbor therapeutically actionable alterations undetected in their matched primaries. Key clinicopathological and genomic alterations in our cohort were externally validated. In summary, our analysis highlights the complexity of clinicopathological features and tumor genomics in LUAD organotropism.

Low level of antioxidant capacity biomarkers but not target overexpression predicts vulnerability to ROS-inducing drugs

Despite a strong rationale for why cancer cells are susceptible to redox-targeting drugs, such drugs often face tumor resistance or dose-limiting toxicity in preclinical and clinical studies. An important reason is the lack of specific biomarkers to better select susceptible cancer entities and stratify patients. Using a large panel of lung cancer cell lines, we identified a set of "antioxidant-capacity" biomarkers (ACB), which were tightly repressed, partly by STAT3 and STAT5A/B in sensitive cells, rendering them susceptible to multiple redox-targeting and ferroptosis-inducing drugs. Contrary to expectation, constitutively low ACB expression was not associated with an increased steady state level of reactive oxygen species (ROS) but a high level of nitric oxide, which is required to sustain high replication rates. Using ACBs, we identified cancer entities with a high percentage of patients with favorable ACB expression pattern, making it likely that more responders to ROS-inducing drugs could be stratified for clinical trials.

Multi-omics analysis unravels the underlying mechanisms of poor prognosis and differential therapeutic responses of solid predominant lung adenocarcinoma

Background

Solid predominant adenocarcinoma (SPA) has been reported to be a subtype with poor prognosis and unsatisfactory response to chemotherapy and targeted therapy in lung adenocarcinoma (LUAD). However, the underlying mechanisms remain largely unknown and the suitability of immunotherapy for SPA has not been investigated.

Methods

We conducted a multi-omics analysis of 1078 untreated LUAD patients with clinicopathologic, genomic, transcriptomic, and proteomic data from both public and internal cohorts to determine the underlying mechanisms of poor prognosis and differential therapeutic responses of SPA and to investigate the potential of immunotherapy for SPA. The suitability of immunotherapy for SPA was further confirmed in a cohort of LUAD patients who received neoadjuvant immunotherapy in our center.

Results

Along with its aggressive clinicopathologic behaviors, SPA had significantly higher tumor mutation burden (TMB) and number of pathways altered, lower TTF-1 and Napsin-A expression, higher proliferation score and a more immunoresistant microenvironment than non-solid predominant adenocarcinoma (Non-SPA), accounting for its worse prognosis. Additionally, SPA had significantly lower frequency of therapeutically targetable driver mutations and higher frequency of EGFR/TP53 co-mutation which was related to resistance to EGFR tyrosine kinase inhibitors, indicating a lower potential for targeted therapy. Meanwhile, SPA was enriched for molecular features associated with poor response to chemotherapy (higher chemoresistence signature score, lower chemotherapy response signature score, hypoxic microenvironment, and higher frequency of TP53 mutation). Instead, muti-omics profiling revealed that SPA had stronger immunogenicity and was enriched for positive biomarkers for immunotherapy (higher TMB and T cell receptor diversity; higher PD-L1 expression and more immune cell infiltration; higher frequency of gene mutations predicting efficacious immunotherapy, and elevated expression of immunotherapy-related gene signatures). Furthermore, in the cohort of LUAD patients who received neoadjuvant immunotherapy, SPA had higher pathological regression rates than Non-SPA and patients with major pathological response were enriched in SPA, confirming that SPA was more prone to respond to immunotherapy.

Conclusions

Compared with Non-SPA, SPA was enriched for molecular features associated with poor prognosis, unsatisfactory response to chemotherapy and targeted therapy, and good response to immunotherapy, indicating more suitability for immunotherapy while less suitability for chemotherapy and targeted therapy.

Mass Spectrometry-Based Proteomics Workflows in Cancer Research: The Relevance of Choosing the Right Steps

The qualitative and quantitative evaluation of proteome changes that condition cancer development can be achieved with liquid chromatography-mass spectrometry (LC-MS). LC-MS-based proteomics strategies are carried out according to predesigned workflows that comprise several steps such as sample selection, sample processing including labeling, MS acquisition methods, statistical treatment, and bioinformatics to understand the biological meaning of the findings and set predictive classifiers. As the choice of best options might not be straightforward, we herein review and assess past and current proteomics approaches for the discovery of new cancer biomarkers. Moreover, we review major bioinformatics tools for interpreting and visualizing proteomics results and suggest the most popular machine learning techniques for the selection of predictive biomarkers. Finally, we consider the approximation of proteomics strategies for clinical diagnosis and prognosis by discussing current barriers and proposals to circumvent them.

Proteomics to study cancer immunity and improve treatment

Cancer survival and progression depend on the ability of tumor cells to avoid immune recognition. Advances in the understanding of cancer immunity and tumor immune escape mechanisms enabled the development of immunotherapeutic approaches. In patients with otherwise incurable metastatic cancers, immunotherapy resulted in unprecedented response rates with the potential for durable complete responses. However, primary and acquired resistance mechanisms limit the efficacy of immunotherapy. Further therapeutic advances require a deeper understanding of the interplay between immune cells and tumors. Most high-throughput studies within the past decade focused on an omics characterization at DNA and RNA level. However, proteins are the molecular effectors of genomic information; therefore, the study of proteins provides deeper understanding of cellular functions. Recent advances in mass spectrometry (MS)-based proteomics at a system-wide scale may allow translational and clinical discoveries by enabling the analysis of understudied post-translational modifications, subcellular protein localization, cell signaling, and protein-protein interactions. In this review, we discuss the potential contribution of MS-based proteomics to preclinical and clinical research findings in the context of tumor immunity and cancer immunotherapies.

Clinical proteomics towards multiomics in cancer

Recent technological advancements in mass spectrometry (MS)-based proteomics technologies have accelerated its application to study greater and greater numbers of human tumor specimens. Over the last several years, the Clinical Proteomic Tumor Analysis Consortium, the International Cancer Proteogenome Consortium, and others have generated MS-based proteomic profiling data combined with corresponding multiomics data on thousands of human tumors to date. Proteomic data sets in the public domain can be re-examined by other researchers with different questions in mind from what the original studies explored. In this review, we examine the increasing role of proteomics in studying cancer, along with the potential for previous studies and their associated data sets to contribute to improving the diagnosis and treatment of cancer in the clinical setting. We also explore publicly available proteomics and multi-omics data from cancer cell line models to show how such data may aid in identifying therapeutic strategies for cancer subsets.

Extracellular matrix profiles determine risk and prognosis of the squamous cell carcinoma subtype of non-small cell lung carcinoma

BACKGROUND

Squamous cell carcinoma (SqCC) is a subtype of non-small cell lung cancer for which patient prognosis remains poor. The extracellular matrix (ECM) is critical in regulating cell behavior; however, its importance in tumor aggressiveness remains to be comprehensively characterized.

METHODS

Multi-omics data of SqCC human tumor specimens was combined to characterize ECM features associated with initiation and recurrence. Penalized logistic regression was used to define a matrix risk signature for SqCC tumors and its performance across a panel of tumor types and in SqCC premalignant lesions was evaluated. Consensus clustering was used to define prognostic matreotypes for SqCC tumors. Matreotype-specific tumor biology was defined by integration of bulk RNAseq with scRNAseq data, cell type deconvolution, analysis of ligand-receptor interactions and enriched biological pathways, and through cross comparison of matreotype expression profiles with aging and idiopathic pulmonary fibrosis lung profiles.

RESULTS

This analysis revealed subtype-specific ECM signatures associated with tumor initiation that were predictive of premalignant progression. We identified an ECM-enriched tumor subtype associated with the poorest prognosis. In silico analysis indicates that matrix remodeling programs differentially activate intracellular signaling in tumor and stromal cells to reinforce matrix remodeling associated with resistance and progression. The matrix subtype with the poorest prognosis resembles ECM remodeling in idiopathic pulmonary fibrosis and may represent a field of cancerization associated with elevated cancer risk.

CONCLUSIONS

Collectively, this analysis defines matrix-driven features of poor prognosis to inform precision medicine prevention and treatment strategies towards improving SqCC patient outcome.

Advances in the application of proteomics in lung cancer

Although the incidence and mortality of lung cancer have decreased significantly in the past decade, it is still one of the leading causes of death, which greatly impairs people’s life and health. Proteomics is an emerging technology that involves the application of techniques for identifying and quantifying the overall proteins in cells, tissues and organisms, and can be combined with genomics, transcriptomics to form a multi-omics research model. By comparing the content of proteins between normal and tumor tissues, proteomics can be applied to different clinical aspects like diagnosis, treatment, and prognosis, especially the exploration of disease biomarkers and therapeutic targets. The applications of proteomics have promoted the research on lung cancer. To figure out potential applications of proteomics associated with lung cancer, we summarized the role of proteomics in studies about tumorigenesis, diagnosis, prognosis, treatment and resistance of lung cancer in this review, which will provide guidance for more rational application of proteomics and potential therapeutic strategies of lung cancer.

Evolutionary selection identifies critical immune-relevant genes in lung cancer subtypes

In an evolving population, proliferation is dependent on fitness so that a numerically dominant population typically possesses the most well adapted phenotype. In contrast, the evolutionary "losers" typically disappear from the population so that their genetic record is lost. Historically, cancer research has focused on observed genetic mutations in the dominant tumor cell populations which presumably increase fitness. Negative selection, i.e., removal of deleterious mutations from a population, is not observable but can provide critical information regarding genes involved in essential cellular processes. Similar to immunoediting, "evolutionary triage" eliminates mutations in tumor cells that increase susceptibility to the host immune response while mutations that shield them from immune attack increase proliferation and are readily observable (e.g., B2M mutations). These dynamics permit an "inverse problem" analysis linking the fitness consequences of a mutation to its prevalence in a tumor cohort. This is evident in "driver mutations" but, equally important, can identify essential genes in which mutations are seen significantly less than expected by chance. Here we utilized this new approach to investigate evolutionary triage in immune-related genes from TCGA lung adenocarcinoma cohorts. Negative selection differs between the two cohorts and is observed in endoplasmic reticulum aminopeptidase genes, ERAP1 and ERAP2 genes, and DNAM-1/TIGIT ligands. Targeting genes or molecular pathways under positive or negative evolutionary selection may permit new treatment options and increase the efficacy of current immunotherapy.

Blocking ActRIIB and restoring appetite reverses cachexia and improves survival in mice with lung cancer

Cancer cachexia is a common, debilitating condition with limited therapeutic options. Using an established mouse model of lung cancer, we find that cachexia is characterized by reduced food intake, spontaneous activity, and energy expenditure accompanied by muscle metabolic dysfunction and atrophy. We identify Activin A as a purported driver of cachexia and treat with ActRIIB-Fc, a decoy ligand for TGF-β/activin family members, together with anamorelin (Ana), a ghrelin receptor agonist, to reverse muscle dysfunction and anorexia, respectively. Ana effectively increases food intake but only the combination of drugs increases lean mass, restores spontaneous activity, and improves overall survival. These beneficial effects are limited to female mice and are dependent on ovarian function. In agreement, high expression of Activin A in human lung adenocarcinoma correlates with unfavorable prognosis only in female patients, despite similar expression levels in both sexes. This study suggests that multimodal, sex-specific, therapies are needed to reverse cachexia.

Factors affecting outcome in resected EGFR-mutated lung cancer

INTRODUCTION

Long-term data on disease trajectory of EGFR-mutated early-stage non-small cell lung cancer (NSCLC) is still limited. This is relevant in the context of the recently approved introduction of adjuvant EGFR-targeting therapy, specifically osimertinib in resected stage II-III EGFR-mutated NSCLC.

METHODS

Long-term data on patients with resected adenocarcinoma of the lung and known EGFR-status were analysed with focus on site of relapse and detailed cause of death. Patients resected in the period 2006 to 2018 were included.

RESULTS

Of 503 patients (286 (57%) females, median age 67.3 years), 62 (12%) harboured an EGFR-mutation, 286 (57%) were in stage I. After a median follow-up of 8.0 years, 241 (48%) patients relapsed. Recurrence occurred in 30% and 53% of EGFR-positive stage IA and IB patients, respectively. Median overall survival was longer in EGFR-mutated versus non-mutated patients (128 versus 88 months). The recurrence rate, time to recurrence and rate of brain metastases was not different between EGFR-mutated and non-mutated groups. Median time from recurrence to death was longer in EGFR-mutated patients (31 months) compared with non-mutated patients (15 months). More patients without EGFR-mutation succumbed to non-cancer related death (18%) compared to patients with EGFR-mutations (8%).

CONCLUSIONS

The recurrence pattern in EGFR-mutated and non-mutated NSCLC-patients is similar and the rate is high in early stages. Time from recurrence to death and overall survival is longer in the EGFR-mutated group, due to lower risk of non-lung cancer deaths, and efficient treatment upon relapse.

Proteomic Profiling and Biomarker Discovery in Colorectal Liver Metastases

Colorectal liver metastases (CRLM) are the leading cause of death among patients with metastatic colorectal cancer (CRC). As part of multimodal therapy, liver resection is the mainstay of curative-intent treatment for select patients with CRLM. However, effective treatment of CRLM remains challenging as recurrence occurs in most patients after liver resection. Proposed clinicopathologic factors for predicting recurrence are inconsistent and lose prognostic significance over time. The rapid development of next-generation sequencing technologies and decreasing DNA sequencing costs have accelerated the genomic profiling of various cancers. The characterisation of genomic alterations in CRC has significantly improved our understanding of its carcinogenesis. However, the functional context at the protein level has not been established for most of this genomic information. Furthermore, genomic alterations do not always result in predicted changes in the corresponding proteins and cancer phenotype, while post-transcriptional and post-translational regulation may alter synthesised protein levels, affecting phenotypes. More recent advancements in mass spectrometry-based technology enable accurate protein quantitation and comprehensive proteomic profiling of cancers. Several studies have explored proteomic biomarkers for predicting CRLM after oncologic resection of primary CRC and recurrence after curative-intent resection of CRLM. The current review aims to rationalise the proteomic complexity of CRC and explore the potential applications of proteomic biomarkers in CRLM.

Proteomic Analysis of Lung Cancer Types—A Pilot Study

Lung cancer is the leading cause of tumor-related mortality, therefore significant effort is directed towards understanding molecular alterations occurring at the origin of the disease to improve current treatment options. The aim of our pilot-scale study was to carry out a detailed proteomic analysis of formalin-fixed paraffin-embedded tissue sections from patients with small cell or non-small cell lung cancer (adenocarcinoma, squamous cell carcinoma, and large cell carcinoma). Tissue surface digestion was performed on relatively small cancerous and tumor-adjacent normal regions and differentially expressed proteins were identified using label-free quantitative mass spectrometry and subsequent statistical analysis. Principal component analysis clearly distinguished cancerous and cancer adjacent normal samples, while the four lung cancer types investigated had distinct molecular profiles and gene set enrichment analysis revealed specific dysregulated biological processes as well. Furthermore, proteins with altered expression unique to a specific lung cancer type were identified and could be the targets of future studies.

Obtaining Complete Human Proteomes

Proteins are the molecular effectors of the information encoded in the genome. Proteomics aims at understanding the molecular functions of proteins in their biological context. In contrast to transcriptomics and genomics, the study of proteomes provides deeper insight into the dynamic regulatory layers encoded at the protein level, such as posttranslational modifications, subcellular localization, cell signaling, and protein-protein interactions. Currently, mass spectrometry (MS)-based proteomics is the technology of choice for studying proteomes at a system-wide scale, contributing to clinical biomarker discovery and fundamental molecular biology. MS technologies are continuously being developed to fulfill the requirements of speed, resolution, and quantitative accuracy, enabling the acquisition of comprehensive proteomes. In this review, we present how MS technology and acquisition methods have evolved to meet the requirements of cutting-edge proteomics research, which is describing the human proteome and its dynamic posttranslational modifications with unprecedented depth. Finally, we provide a perspective on studying proteomes at single-cell resolution. Expected final online publication date for the Annual Review of Genomics and Human Genetics, Volume 23 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.