Despite genomics delivering major advances in cancer prognostics, treatment and diagnostics, it only provides a limited, static view of the disease. This static view results in key biology being missed when trying to reliably predict patient response to therapy and how the cancer is likely to progress. These limitations can be attributed to the fact that the molecular drivers of cancer are derived from both DNA and proteins. This led to calls for a focus on proteomics in cancer research, calls which were met last year with the inclusion of a proteomics focused project in the Moonshot for Cancer. The project, named Applied Proteogenomics Organizational Learning and Outcomes (APOLLO), will combine genetic sequencing and proteomic analysis of tumors to develop clinically actionable molecular panels for precision medicine and personalized health.
Deciphering the Cancer Proteome
APOLLO sets out to build on the ground-breaking research laid down by The Cancer Genome Atlas (TCGA) by including high-resolution, high-acuity proteo measurements with a focus on understanding metastasis, chemo-resistance and patient response in clinical trials. According to Dr Tom Conrads, co-investigator at the DoD Gynecologic Cancer Center of Excellence, one of the labs at the centre of the APOLLO project, “It’s exciting to see proteomics standing on a similar ground in the dialogue as genomics has been for the past 15 years”. He went on to explain that “APOLLO represents a very large project, a grand challenge, of making proteogenomic measurements across 8,000 cancer patients over the next 5 years. We are not just looking to reclassify cancer with APOLLO, we are really looking to arrive at clinically actionable end points.”
Highlighted in a 2014 Nature paper, that looked at colon tumour samples from the TCGA, one of the key issues this new proteomic approach will help to overcome is the low correlation between RNA expression and protein abundance. Dr Conrads commented, “We know [from studies like this] that RNA analyses do not translate to the end game, which is ultimately protein abundance. That’s a problem because all of the hypotheses we generate from RNA-based expression data could be red herrings”. Furthermore, it is the proteins that actually do the work of the cell and represent the structural cellular machinery. It is the proteins that comprise most of the biomarkers that are measured to detect cancers, constitute the antigens that drive immune response and inter and intracellular communications. And, it is the proteins that are the drug targets for nearly every targeted therapy that is being evaluated in cancer trials today.
There may also be other opportunities to build on TCGA. This Nature Communications paper from 2015 revealed an interesting correlation between the extent of purity in samples and the mutational load in the cancer cells. Here, purer tumor samples, that consisted mostly of cancerous cells, had a lower overall mutational burden. They also found that purity influenced the stage and grade of cancer. In select cases, such as in low grade glioma, patients with more impure tumour samples had statistically far worse outcomes than patients with purer tumours. All of this is important because TCGA had a cut off of about 70% purity for a sample to be included in the program. Therefore, the project may have inadvertently focused on profiling tumours which had better outcomes. With that in mind, Dr Conrads says, “We need to include these considerations in the proteogenomes we profile for cancer patients so we have better inclusion of all tumours.”
Molecular Alterations Linked to Race-specific Cancer Outcomes
Greater than 80 percent of the samples from TCGA were from Caucasian patients. In contrast, major subprojects in the APOLLO project are focused on including samples from a broader racial and ethnic background. Dr Conrads commented, “We know from the SEER database, and others, that there are clear racial disparities in cancer outcomes. One of the most extreme being in Endometrial cancer where African Americans have an overall 22% worse survival rate when they get uterine cancer compared to Caucasian patients.”
Leveraging a proteogenomics approach, a recent Cancer paper, set out to explore this difference at the molecular level. By combining LC-MS and RNA-Seq data the team revealed significant differences in candidate proteins and transcripts between black and white patients. Interestingly, they found a number of transcript alterations between black and white patients that were significantly associated with progression-free survival (PFS). Two of which, SERPINA4 and BET1L were identified as correlating with better PFS specifically in white patients. A serine protease inhibitor, SERPINA4 has previously been shown to inhibit angiogenesis as well as tumor growth in a range of cancers. BET1L is a protein receptor responsible for regulating vesicular transport within the golgi apparatus. GWAS studies have recently linked an SNP in the 3’-untranslated region of BET1L with a decreased risk of developing uterine fibroids in women of European American descent. On the other hand, a theoretical protein-coding gene that is largely of unknown function called FAM228B was identified as a black-specific marker for improved PFS. Finally, LIG3 was found to be associated with poor PFS for black patients but, improved PFS in whites. LIG3 regulates a highly error prone subtype of alternative nonhomologous end joining DNA repair, termed microhomology-mediated end joining, that can result in an elevated risk of genome instability and increased cancer risk. It is therefore proposed that LIG3—associated microhomology-mediated end joining signalling may play a greater role in black patients than in whites. This finding will now be explored further in a number of ongoing studies.
Ending Cancer As We Know It
Up until recently, Conrads, like many others in the field, saw proteomics at a similar stage as genomics in the mid-1990s. Namely, a limited number of labs with relatively low levels of funding working on developing technology rather than participating in clinical research. However, our ability to map and understand the proteome within the tumor tissue microenvironment is advancing rapidly. Enabled by recent developments in technology and informatics, heavily supported by vendor companies, researchers are now able to quantity over 10,000 proteins in a single experiment. Alongside this, developments in multiplexed proteomic technologies like reverse phase protein microarray enable previously unprecedented real-time molecular profiling of tumour cells. This allows researchers to more accurately ascertain which cells in a sample are producing which protein, a key step in understanding the disease. By combining these developments, and many others, we can now begin to leverage a “multi-omics” approach with the goal of realising the promise of the Cancer Moonshot, “Ending cancer as we know it.” In light of these developments, Dr Conrads holds a positive outlook for the field “I think we are all optimistic that while the TCGA and genomics based information has led to some really huge increases in our understanding of the nature of cancer and, its heterogeneity. We hope that taking that next step in to clinical actionability will be enabled by including proteomic measurements.”