Harvard: Prediagnostic Biomarkers of Smoking-Associated Lung Cancer

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Harvard Medical School Collaboration Discovers Prediagnostic Biomarkers of Smoking-Associated Lung Cancer

It’s real! 36 types in total! Harvard Medical School Collaboration Discovers Prediagnostic Biomarkers of Smoking-Associated Lung Cancer

Introduction: Identification of risk biomarkers improves early detection of smoking-associated lung cancer.

In 731 smoking-matched case-control sets from six prospective cohorts in the United States, Europe, Singapore, and Australia, the researchers measured 392 to 1,162 proteins in blood samples collected up to 3 years before diagnosis.

Thirty-six proteins with independent and reproducible associations with the risk of an upcoming lung cancer diagnosis were subsequently identified.

The researchers mapped these 36 proteins to hallmarks of cancer and found that they were most commonly involved in the activation of invasion and metastasis, proliferative signaling, pro-tumor inflammation, and angiogenesis.

Recently, researchers from Harvard Medical School published a paper titled “The blood proteome of imminent lung cancer diagnosis ” in the internationally renowned journal “Nature Communications”. Their epidemiological properties, the biological pathways to which they belong, and their known relevance in carcinogenesis.

Harvard Medical School Collaboration Discovers Prediagnostic Biomarkers of Smoking-Associated Lung Cancer https://www.nature.com/articles/s41467-023-37979-8

Research Background

Lung cancer is the leading cause of cancer death worldwide.

The 5-year survival rate is 20%, but the 5-year survival rate of early lung cancer (stage 1~2) is 60%, and the 5-year survival rate of advanced lung cancer (stage 4) is 6%.

In the United States, from 2013 to 2016, the death rate from lung cancer decreased by 6% per year.

This improvement can be attributed to advances in the diagnosis and treatment of patients with early and advanced lung cancer.

Improvements in surgical techniques including stereotactic body radiation therapy (SBRT) and adjuvant chemotherapy have improved outcomes for patients with early-stage disease, while patients with locally advanced disease have benefited from chemoradiotherapy, adjuvant immunotherapy, and the introduction of neoadjuvant immune checkpoint inhibitors (ICIs) .

Although the development of combined targeted and immunotherapies has improved short-term survival, most lung cancer patients are diagnosed with advanced disease, making cure nearly impossible.

Despite advances in lung cancer treatment, improving early detection is the most promising strategy for improving long-term survival.

Low-dose computed tomography (LDCT) screening has the potential to substantially increase the proportion of early-stage lung cancer patients who can be definitively treated.

LDCT screening was able to reduce lung cancer mortality in high-risk individuals with a history of smoking in several randomized trials, but questions remain, including how best to identify and reach those who may benefit from screening, and how to manage Indeterminate pulmonary nodules detected by LDCT.

The advent of low-dose CT screening and the introduction of targeted therapy have highlighted the need to identify biomarkers of lung cancer that can be used to:

(i) identify high-risk individuals who may benefit from screening,

(ii) guide low-risk Confirmatory workup and nodule management after dosimetry CT screening,

(iii) selection of optimal treatment regimen and monitoring of treatment response.

In 2018, the National Cancer Institute funded the integrated Analysis of Lung Cancer Etiology and Risk (INTEGRAL) project, an ambitious program focused on developing biomarkers to refine LDCT Inclusion criteria for screening and confirmatory workup after LDCT.

Here, researchers present the results of an initial large-scale analysis aimed at identifying circulating protein biomarkers associated with impending lung cancer diagnosis in the general population with a history of smoking.

Using a high-throughput proteomics approach, we screened more than 1000 circulating proteins in blood samples drawn three years before diagnosis in the Lung Cancer Cohort Consortium (LC3).

Here, the researchers focused on identifying proteins strongly associated with lung cancer diagnosis risk, and then characterizing their epidemiology, the biological pathways to which they belong, and their known relevance in carcinogenesis.

Research process

In this study, 1162 circulating proteins were analyzed, and 67 proteins were found to be associated with lung cancer risk after multiple testing.

Using a resampling algorithm to simulate multiple iterations of the split-sample discovery and replication process, the researchers identified 36 proteins with replicable associations with the risk of an upcoming lung cancer diagnosis, 35 of which were positively associated with risk.

Among the 36 markers, 6 have been reported to be associated with lung cancer in pre-diagnostic samples, including several well-known tumor markers such as CEACAM5/CEA and CA-125/MUC-16, as well as IL6, CDCP1, CXCL9 and CXCL13.

The researchers describe the epidemiological properties of the identified proteins and their association with known risk factors such as smoking.

Despite cross-sectional associations of several proteins with smoking history, researchers found limited evidence of heterogeneity in risk associations for most of the 36 markers when stratified by smoking status, with additional adjustment for smoking characteristics has little impact.

However, the researchers found that the risk associations for many of the 36 markers were stronger when they were measured in blood closer to diagnosis. This is a marker that predicts impending disease, not the cause of the disease.

When evaluating the known mechanistic roles of these 36 proteins, the researchers found that they have a wide range of molecular functions, including multiple growth factors (HGF, MK, IGFBP-1, IGFBP-2, TGF-α, VEGFA), tumor necrosis Factor receptors (TNFRSF6B, TNFRSF13B), chemokines and cytokines (CXL17, GDF-15, OSM, SCF).

When correlating the identified markers with hallmarks of cancer, the researchers found that the most common marker was “activated invasion and metastasis” (19 markers), which is related to the regulation of the extracellular matrix during metastasis, among others by MMP12 and U-PAR. of known proteins.

To better understand the relationships among the 36 markers, we performed a LASSO-based sparse graph network analysis and observed specific associations between 12 proteins in lung cancer cases that were not present in controls.

To understand why circulating concentrations of the identified proteins correlated with lung cancer diagnosis, and to assess whether they might be specific to lung cancer (rather than cancer at other sites), the researchers used published expression data from a range of normal and tumor tissues.

Harvard Medical School Collaboration Discovers Prediagnostic Biomarkers of Smoking-Associated Lung Cancer Biological context of 36 proteins associated with risk of impending lung cancer diagnosis

Significance

Taken together, after screening 1162 proteins, the researchers identified 36 impending lung cancer markers with broad functions and associations with cancer markers.

This study provides a potential view of the blood proteome for the diagnosis of smoking-related lung cancer, and can provide a reference for the search for early protein markers of lung cancer.

References:

https://www.nature.com/articles/s41467-023-37979-8

Harvard Medical School Collaboration Discovers Prediagnostic Biomarkers of Smoking-Associated Lung Cancer

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