Background
RAS transcriptional diversity
Clonal diversity
Limitations of clonal diversity
Immunological diversity
Conclusion
References
Further reading
Lung cancer is the most common deadly cancer, with 1.6 million cases arising every year. Diversity of many kinds affects the incidence, course, and outcome of lung cancer. Morphologically, lung cancers are of four different types – squamous cell, small cell, large cell, and adenocarcinomas.
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Background
Squamous and small cell tumors of the lung make up about a third and a fifth (30% and 18%, respectively) of lung cancers, both arising from airway epithelium. Adenocarcinomas comprise another 30%, and originate in the small airway epithelium. The remaining 10% are large cell tumors, mostly peripheral in location.
Small cell cancers respond well to chemotherapy at first, but typically recur. The recurrences are resistant to chemotherapy, and spread systemically, leading to the patient’s death.
In contrast, nonsmall cell lung cancers are unpredictable in their diagnostic classification and prognosis. Thus, even when the primary tumor is successfully removed in toto, metastatic cancer leads to death in half of the patients.
Much research has shown that diversity at genomic, epigenetic and gene expression levels is associated with poor survival for nonsmall cell lung tumors.
RAS transcriptional diversity
Oncogenes of the RAS family occur in a fifth of all tumors in humans, driving tumorigenesis and tumor progression. One type called KRAS mutations have been identified as disease activators in a third of lung adenocarcinomas. However, there is diversity in the contribution of KRAS to lung cancer prognosis.
This is probably because the RAS pathways are heavily modulated by other factors. This discrepancy is highlighted by the occurrence of RAS oncogene activation in 84% of lung adenocarcinomas, even though 65% possess wild-type KRAS genes.
High RAS activity is associated with a poor response to chemotherapy and a poor outcome. RAS84 is a transcriptional signature that closely correlates with RAS oncogenic activity.
Thus, some scientists think that “RAS84 captures RAS oncogenic activity in tumour samples better than the mutational status of KRAS” and could help stratify patients in terms of survival, cancer progression, and resistance to treatment.
Clonal diversity
Tumors begin with a single cancer cell, but with tumor cell proliferation, clonal diversity begins to manifest itself. That is, tumors often contain different groups of cancer cells that demonstrate variable responses to the same treatment.
This clonal diversity has come to light via single-cell sequencing technology. With the emergence of targeted therapies and personalized medicine, it is essential to understand intratumor diversity, because these therapies act on cells containing specific mutations. Other tumor cells lacking these genetic elements will therefore survive the therapy, and eventually cause recurrence.
“Perhaps in the future, we can design better therapy combinations to prevent those subclones from surviving and causing relapse,” says Dr. Koichi Takahashi, physician and researcher.
Using single-cell RNA sequencing techniques, scientists have shown that chemotherapy often causes treated cells to enter a state of hibernation using the repair and damage genes. This allows them to survive the toxic therapy.
These cells show a different signature, indicative of alveolar cell regeneration, compared to cells that survive and proliferate even during therapy. The latter also suppress the host immune response in the tumor microenvironment, while the former display an inflammatory state, infiltrated by active T cells.
However, the dormancy pathway offers a potential therapeutic target via the WNT/β-catenin signaling cascade that is activated by cell injury and survival signals. Conversely, the kynurenine pathway is characteristically upregulated in progressive disease while on therapy, which might also present a different targetable point, albeit for a brief period.
Researcher Trevor Bivona says, “Putting tumor heterogeneity front and center would better equip clinicians with information that allows for a high-resolution window into the evolution of tumors during therapy, and help us use such a roadmap to intervene more proactively to better control tumors and help patients.”
Even otherwise, research indicates that the number of subclones characterized by different mutations is a more important prognostic factor than the identity of each subclone, in some though not all tumors. This could be the result of higher genomic instability, which in turn may promote the odds of malignant transformation.
However, this is opposed by a phenomenon called clonal sweeps, where highly adapted clones are born when their mutations increase in frequency to become fixed. This reduces genetic variability in nearby genetic sequences.
Such sweeps may reduce clonal diversity within aggressive tumors, though sweep frequency is modulated by clonal interference.
Further work is necessary to understand how genetic diversity interacts with more conventional prognostic markers such as tumor grade and stage. It is well-known that the mean cell division rate is a relatively reliable marker of future tumor growth, because it correlates with the tumor grade.
Clonal diversity in tumors
Limitations of clonal diversity
However, the use of clonal diversity as a prognostic marker is unreliable due to the unpredictability of tumor progression between patients in a cohort, or due to low levels of variability between patients.
Clone expansion is limited also by its interactions with other nearby clones, and by its proximity to the tumor edge. Thus, the strength and usefulness of correlation between diversity and tumor growth depends on the stage at which diversity is measured.
When measured in early tumors, clonal diversity is associated positively with the subsequent growth rate of the tumor, but negatively when measured at later stages. Again, all clones do not contribute equally to the growth of the tumor.
Those that are fit and spread rapidly beyond the advancing edge, or those arising near the edge, are more likely to boost tumor growth than those in the tumor core.
Further, when assessed at intermediate tumor size, clonal diversity is correlated with tumor growth only with low clonal turnover. This is due to a low rate of driver mutations, reduced driver fitness, and small carrying capacity.
Clonal diversity also provides insight into the evolution of the cancer. For instance, the transcriptional Cosmic Signature 4, which is closely related to smoking, predominates in trunk mutations, indicating the strong influence of smoking on the early mutations responsible for many lung cancers.
Conversely, it is much reduced in non-trunk mutations, where Cosmic Signature 3, associated with double-stranded DNA break repair defects, comprises the largest share.
Immunological diversity
Another type of diversity is related to the levels of immune infiltrate, which differs between small cell (lower T cell infiltration) and nonsmall cell (higher infiltration) lung tumors. Nonsmall cell tumors show loss of heterozygosity (LOH), or somatic mutations, that drive immune escape or resistance to immune checkpoint blockade (ICB) therapy.
HLA-1-targeting CD8+ cytotoxic T cell responses are key to ICB function. However, cytotoxic CD4+ T cells may drive anti-tumor activity targeted to HLA-II-bearing non-small cell lung cancer cells. In this way, despite CD8+ T cell evasion, the CD4+ response may drive the ICB response. This could explain why some such tumors have a better prognosis despite a higher tumor mutational burden.
Diverse gene expression profile
Lung tumors have heterogeneous morphology, and initial biopsy-based diagnoses are known to change following the examination of the tissue removed during the definitive surgery. Mixed tumors are also well-known, such as combined small cell-non-small cell tumors or adenosquamous carcinomas.
Gene expression patterns have been used to classify lung cancers within the four standard categories into subgroups that show different levels of differentiation and have varying prognoses. This helps determines tumor cell differentiation and behavior.
For instance, the gene expression profile in morphologically similar adenocarcinomas may successfully predict the tumor grade and clinical stage, and therefore the chances of survival, in well-differentiated vs poorly differentiated tumors. Even more, it could identify a third subset with poor differentiation but good survival rates.
Such gene markers may help to standardize morphological tumor grading, which is at present necessarily affected by interobserver variability, and is often a suboptimal guide to therapy.
Ethnic diversity
Recent research suggests significant ethnic differences between lung cancers (adenocarcinoma and squamous carcinomas) in Asian and Western patients. The two most common mutations in nonsmall cell lung cancers affect the epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK) loci.
In one study from China, the rate of P/LP germline mutations was higher among Chinese cancers compared to Western cancers. Again, some genes were unique to Chinese cancers and others to the Western cancers.
Secondly, only about a third of germline mutations seen in Western tumors were present in Chinese patients, and even so, the prevalence of various somatic mutations in those with germline mutations differs from those without. The BRCA2 germline mutations, and EGFR somatic mutations, are also more common in Asiancancers. However, EGFR germline mutations are much less common in Chinese patients with EGFR somatic mutations, compared to Western patients.
These genomic differences could be due to both ethnic and exposure factors, which vary with the genetic population and geographical location. The obvious inference is that clinical studies and trials should include a range of ethnic and racial backgrounds to ensure generalizability.
In the US, Blacks make up about a seventh of all lung cancer patients, but only 3% of clinical trial participants. To help address this, the American Lung Association rolled out its “Awareness, Trust and Action” campaign in January 2022. One of the sponsoring companies’ officials, Wendy Short Bartie, says, “Education is an essential component to improving diversity in clinical trial enrollment to ensure that all people affected by cancer can equally benefit from the latest science and treatments.”
Conclusion
Geographical disparities in socioeconomic resources, the cost of targeted therapies and molecular diagnosis, and differences in the testing methods used, account for much of the variation in results between different populations and regions. Detailed collaborative genomic mapping and cost management spanning the continents will be essential to identify and exploit cancer-relevant loci.
“It is anticipated that expanding knowledge of inherited and somatic genomics will further advance our understanding of cancer genetics and lead to improved strategies for prevention, detection, and treatment of cancer.” Screening strategies for some cancers could change significantly with such knowledge.
Resources
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- Noble, R. et al. (2020). When, why and how tumour clonal diversity predicts survival. Evolutionary Applications. doi: https://doi.org/10.1111%2Feva.13057. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7428820/.
- Lau, D. et al. (2022). Integration of tumor extrinsic and intrinsic features associates with immunotherapy response in non-small cell lung cancer. Nature Communications. doi: https://doi.org/10.1038/s41467-022-31769-4. https://www.nature.com/articles/s41467-022-31769-4.
- Peng, W. et al. (2022). Clinical and genomic features of Chinese lung cancer patients with germline mutations. Nature Communications. doi: https://doi.org/10.1038/s41467-022-28840-5. https://www.nature.com/articles/s41467-022-28840-5.
- Ornstein, C. (2022). The importance of representation in lung cancer clinical trials. Each Breath. https://www.lung.org/blog/cancer-clinical-trials-diversity.
- Alvarez, J. (2020). Mapping genetic diversity of lung tumors over time may lead to more effective therapies. https://www.ucsf.edu/news/2020/09/418376/mapping-genetic-diversity-lung-tumors-over-time-may-lead-more-effective.
Further reading
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