Skip to main content
NCBI home page
The Oncologist logoLink to The Oncologist
. 2018 Jul 17;24(3):319–326. doi: 10.1634/theoncologist.2018-0117

Impact of Patient Age on Molecular Alterations of Left‐Sided Colorectal Tumors

Alberto Puccini a,b, Heinz‐Josef Lenz a, John L Marshall c, David Arguello d, Derek Raghavan e, W Michael Korn d, Benjamin A Weinberg c, Kelsey Poorman d, Arielle L Heeke c, Philip A Philip f, Anthony F Shields f, Richard M Goldberg g, Mohamed E Salem e,*
PMCID: PMC6519749  PMID: 30018131

To better understand the disease biology and identify molecular targets for young patients with metastatic colorectal cancer, this study explored the effect of age on the tumor biology of left‐sided colorectal cancer. This is the first study to investigate the molecular differences between younger and older adults and aimed to broaden insights into the disease biology and potential biomarkers that might be involved in early onset colorectal cancer.

Keywords: Colorectal cancer, Early‐onset, Microsatellite instability, Tumor mutational burden, Cancer syndromes, Histone modifiers

Abstract

Background.

The incidence of colorectal cancer (CRC) in younger patients is rising, mostly due to tumors in the descending colon and rectum. Therefore, we aimed to explore the molecular differences of left‐sided CRC between younger (≤45 years) and older patients (≥65).

Subjects, Materials, and Methods.

In total, 1,126 CRC tumor samples from the splenic flexure to (and including) the rectum were examined by next‐generation sequencing (NGS), immunohistochemistry, and in situ hybridization. Microsatellite instability (MSI) and tumor mutational burden (TMB) were assessed by NGS.

Results.

Younger patients (n = 350), when compared with older patients (n = 776), showed higher mutation rates in genes associated with cancer‐predisposing syndromes (e.g., Lynch syndrome), such as MSH6 (4.8% vs. 1.2%, p = .005), MSH2 (2.7% vs. 0.0%, p = .004), POLE (1.6% vs. 0.0%, p = .008), NF1 (5.9% vs. 0.5%, p < .001), SMAD4 (14.3% vs. 8.3%, p = .024), and BRCA2 (3.7% vs. 0.5%, p = .002). Genes involved in histone modification were also significantly more mutated: KDM5C (1.9% vs. 0%, p = .036), KMT2A (1.1% vs. 0%, p = .033), KMT2C (1.6% vs. 0%, p = .031), KMT2D (3.8% vs. 0.7%, p = .005), and SETD2 (3.2% vs. 0.9%, p = .039). Finally, TMB‐high (9.7% vs. 2.8%, p < .001) and MSI‐high (MSI‐H; 8.1% vs. 1.9%, p = .009) were more frequent in younger patients.

Conclusion.

Our findings highlight the importance of genetic counseling and screening in younger CRC patients. MSI‐H and TMB‐high tumors could benefit from immune‐checkpoint inhibitors, now approved for the treatment of MSI‐H/deficient mismatch repair metastatic CRC patients. Finally, histone modifiers could serve as a new promising therapeutic target. With confirmatory studies, these results may influence our approach to younger adults with CRC.

Implications for Practice.

The increasing rate of colorectal cancers (CRC), primarily distal tumors, among young adults poses a global health issue. This study investigates the molecular differences between younger (≤45 years old) and older (≥65) adults with left‐sided CRCs. Younger patients more frequently harbor mutations in genes associated with cancer‐predisposing syndromes. Higher rates of microsatellite instability‐high and tumor mutational burden‐high tumors occur in younger patients, who could benefit from immune‐checkpoint inhibitors. Finally, histone modifiers are more frequently mutated in younger patients and could serve as a new promising therapeutic target. This study provides new insights into mutations that may guide development of novel tailored therapy in younger CRC patients.

Introduction

Colorectal cancer (CRC) is the third most common cancer and the fourth leading cause of cancer‐related death worldwide [1]. In the last 2 decades, adults aged ≥50 years have experienced a decrease in CRC incidence and mortality, while people aged <50 years show the opposite trend [2]. It has been estimated that in 2030, incidence rates of colon and rectal cancers will increase by 90% and 124%, respectively, in patients aged 20–34 years and by 27.7% and 46.0%, respectively, in patients aged 35–49 years [3]. The cause remains unknown, although lack of screening, obesity, physical inactivity, and Western diets may play a crucial role in early‐onset CRC. Therefore, further investigations into causality are necessary to develop potential preventive strategies. Broader molecular tumor profiling should also be explored to identify biomarkers and therapeutic targets unique to younger CRC patients.

Clinicopathological differences between younger and older patients may be explained by underlying different molecular patterns [4], although data regarding the molecular features of sporadic early‐onset CRC are limited and controversial [5]. On the other hand, the pathogenesis of early‐onset CRC is well characterized in individuals with an inherited CRC syndrome, present in around 5%–10% of patients with CRC [6].

Frequencies of TP53, APC, BRAF, and KRAS mutations are similar in both younger and older adults [7]. Tumors in younger adults show higher mutation rates of FBXW7 and POLE [8], are more frequently. The CpG island methylator phenotype (CIMP)‐low [9] and are characterized by higher frequencies of LINE‐1 hypomethylation [10], [11]. Although the majority of early‐onset CRCs are microsatellite stable, microsatellite instability (MSI) is observed in 20%–40% of early‐onset CRCs and is dependent on the age of onset [12]. Most MSI‐high (MSI‐H) tumors in younger patients are associated with Lynch syndrome, harboring a characteristic germline mutation in one of the mismatch repair (MMR) genes, and are BRAF wild‐type. Recently, in a study of 450 patients, Pearlman et al. [13] showed a high frequency of a range of germline mutations (16%) among early‐onset CRCs. Moreover, they showed that deficient‐MMR (dMMR) tumors harbored a different mutational pattern from proficient‐MMR (pMMR) tumors.

One compounding issue is that no global consensus exists on the age‐definition of early‐onset CRC [14]. Although some authors suggest using <50 years of age, corresponding to the CRC screening age in average‐risk populations, age cutoffs vary widely in published studies, making comparisons challenging. Patients younger than 50 years of age are usually diagnosed with more advanced disease compared with those ≥50 years, likely due to delays in symptom recognition and diagnostic workup [15]. Moreover, younger patients tend to present with more histologically aggressive tumors (e.g., mucinous, signet ring cell, and/or poorly differentiated) [16]. However, it is uncertain whether these characteristics are related to worse outcome in young patients. Although contradictory results have been highlighted [17], [18], a range of different studies show better outcomes in terms of CRC‐specific survival in younger patients when compared with their older counterparts [19].

It is important to note that for individuals aged <50 years, the increasing incidence rates are mostly due to tumors occurring in the descending colon and rectum [20], and tumor sidedness has emerged as an important prognostic and predictive biomarker in metastatic CRC (mCRC). Indeed, the differences between left‐ and right‐sided colon cancer in terms of embryology, etiology, and molecular and clinical features have already been demonstrated in various studies [21], [22], [23], [24], [25], [26]. Accordingly, proximal and distal colon cancer may also respond differently to first‐line treatment with biologics in the metastatic setting [25].

In order to better understand the disease biology and identify molecular targets for young patients with mCRC, we explored the impact of age on the tumor biology of left‐sided CRC, defined as CRC from the splenic flexure to (and including) the rectum.

To our knowledge, this is the first study to investigate the molecular differences between left‐sided CRCs from younger (≤45 years) versus older (≥65 years) adults, aimed at broadening insights into the disease biology and potential biomarkers that might be involved in early‐onset CRC.

Subjects, Materials, and Methods

Patients

This analysis included 2,413 left‐sided colorectal tumors profiled at Caris Life Sciences between 2015 and 2017. Tumor tissue was formalin‐fixed and paraffin‐embedded (FFPE). Both specimen and tumor quality were confirmed by a board‐certified pathologist using hematoxylin and eosin staining prior to multiplex testing. Immunohistochemistry (IHC) assessed protein expression; in situ hybridization determined gene amplification; and next‐generation sequencing (NGS) evaluated for DNA aberrations (Illumina NextSeq; Illumina, San Diego, CA) or RNA fusions (ArcherDx FusionPlex assay; ArcherDx, Boulder, CO). All molecular techniques met Clinical Laboratory Improvement Amendments/College of American Pathology standards.

Next‐Generation Sequencing

Direct sequencing was performed on genomic DNA isolated from FFPE tumor specimens using the whole‐exome NextSeq platform. An Agilent SureSelect XT assay (Agilent, Santa Clara, CA) was used to enrich 592 whole‐gene targets. All reported variants were detected with >99% confidence at an average depth of at least ×700. The Illumina platform calculated tumor mutational burden (TMB) by evaluating only somatic nonsynonymous missense mutations.

Microsatellite Instability by NGS and Fragment Analysis

MSI was examined using over 7,000 target microsatellite loci and compared with the reference genome hg19 from the University of California, Santa Cruz Genome Browser database. The number of microsatellite loci that were altered by somatic insertion or deletion was counted for each sample. Only insertions or deletions that increased or decreased the number of repeats were considered. Genomic variants in the microsatellite loci were detected using the same depth and frequency criteria as used for mutation detection. MSI‐NGS results were compared with results from over 2,000 matching clinical cases analyzed with traditional polymerase chain reaction‐based methods. The threshold to determine MSI by NGS was determined to be 46 or more loci with insertions or deletions to generate a sensitivity of >95% and specificity of >99%.

Fragment analysis (FA) included fluorescently labeled primers (Promega, Madison, WI) for co‐amplification of seven biomarkers including five mononucleotide repeat markers (BAT‐25, BAT‐26, NR‐21, NR‐24, and MONO‐27) and two pentanucleotide repeat markers (Penta C and D). The mononucleotide markers determined the presence of MSI, and the pentanucleotide markers were utilized for sample mix‐up detection or contamination. A tumor specimen was considered dMMR if two or more mononucleotide repeats were abnormal. If one mononucleotide repeat was abnormal or repeats were identical between the tumor and adjacent normal tissue, then the tumor sample was considered pMMR.

Tumor Mutational Burden by NGS

TMB was measured by counting all nonsynonymous missense mutations found per tumor that had not been previously described as germline alterations (592 genes and 1.4 megabases [MB] sequenced per tumor). The threshold to define TMB‐high was greater than or equal to 17 mutations/MB and was established by comparing TMB with MSI by fragment analysis in CRC cases, based on reports of TMB having high concordance with MSI‐H in CRC [26]. Values below 17 mutations/Mb were considered intermediate (7–16) or low (<7) and were grouped together for chi‐square analysis.

In Situ Hybridization Methods

Using automated staining (Benchmark XT; Ventana, Tucson, AZ) and imaging (BioView, Billerca, MA) techniques, fluorescent and/or chromogenic in situ hybridization assessed ERBB2 (human epidermal growth receptor 2 [HER2]/CEP17 [chromosome 17 centromere] probe) and MET (c‐MET/CEP7 probe; Abbott Molecular/Vysis, Abbott Park, IL) gene copy alterations. The ratio of gene to pericentromeric regions of chromosome 7 (MET) and 17 (HER2) was utilized to determine gene amplification. Cutoffs for amplification were determined according to manufacturer's recommendation (supplemental online Appendix 1).

Immunohistochemistry Analysis

Automated staining techniques (Benchmark XT; Ventana; and AutostainerLink 48; Dako, Carpinteria, CA) and commercially available detection kits were performed on FFPE tumor specimens. Positive and negative controls were included in each analysis to ensure staining efficacy and consistency across batches. Threshold values for positive expression were optimized for each antibody according to the manufacturer's recommendations, accounting for both staining intensity and percentage of tumor cells stained. Details on IHC interpretations have been described previously [27].

Statistical Analysis

Standard descriptive statistics were used for this retrospective analysis. Pearson's chi‐square test was used to obtain p values (IBM SPSS Statistics for Windows, Version 24.0; Released 2016; IBM Corp., Armonk, NY). Only p values ≤.05 were considered statistically significant.

Ethics Statement

Human subjects were de‐identified prior to analysis, with this retrospective research being exempt per Western Institutional Review Board.

Results

Patient Demographics

Of the 2,413 left‐sided CRC samples, 1,126 were included in this analysis: 350 from younger patients (median age 40, range 22–45 years) and 776 from older patients (median age 72, range 65–89 years; Fig. 1). The older cohort was composed of 39.3% (305/776) female patients compared with 52.3% (183/350) in the younger cohort (Table 1).

Figure 1.

image

Open in a new tab

Consort diagram of LCC included in the study.

Abbreviation: LCC, left‐sided colorectal cancer.

Table 1. Patient characteristics.

image

Open in a new tab

Abbreviation: LCC, left‐sided colorectal cancer.

Mutational Profile via Next‐Generation Sequencing

Across the two cohorts, the most frequently mutated genes included the following: APC (81.8%), TP53 (74.6%), KRAS (46.4%), ARID1A (19.4%), PIK3CA (13.4%), FBXW7 (11.2%), SMAD4 (10.1%), ATM (6.3%), NRAS (4.9%), and BRAF (4.6%; Fig. 2). There were no significant differences in mutation frequencies of these genes between younger and older patient specimens. However, numerous genes that are associated with cancer‐predisposing syndromes, such as Lynch syndrome, also known as hereditary nonpolyposis colorectal cancer (HNPCC), neurofibromatosis type 1 (NF1), PTEN hamartoma tumors syndrome (PHTS), tuberous sclerosis complex (TSC), and hereditary breast ovarian cancer syndrome (HBOC), were found to carry higher mutations rates in younger compared with older patients. Specifically, MSH6 (4.8% vs. 1.2%, p = .005), MSH2 (2.7% vs. 0.0%, p = .004), POLE (1.6% vs. 0.0%, p = .008), NF1 (5.9% vs. 0.5%, p < .001), SMAD4 (14.3% vs. 8.3%, p = .024), PTEN (4.3% vs. 1.4%, p = .03), TSC1 (1.1% vs. 0.0%, p = .031), TSC2 (1.6% vs. 0.2%, p = .048), AKT1 (1.1% vs. 0%, p = .031), and BRCA2 (3.7% vs. 0.5%, p = .002) showed significantly higher mutations in younger versus older patients (Fig. 3; Table 2).

Figure 2.

image

Open in a new tab

Molecular differences between younger and older patients with left‐sided colorectal tumors via next‐generation sequencing analysis.

Figure 3.

image

Open in a new tab

Mutational profile via NGS and protein expression via IHC.

Abbreviations: *, p ≤ .05; **, p ≤ .01; ***, p ≤ .001; FA, fragment analysis; IHC, immunohistochemistry; MSI, microsatellite instability; NGS, next‐generation sequencing.

Table 2. Genes with statistically significant difference in mutation rates between younger and older LCC cohorts via next‐generation sequencing analysis.

image

Open in a new tab

Abbreviation: LCC, left‐sided colorectal cancer.

Furthermore, genes responsible for histone modification were also significantly more frequently mutated in younger than in older patients: CDC73 (1.7% vs. 0%, p = .01), KDM5C (1.9% vs. 0%, p = .036), KMT2A (1.1% vs. 0%, p = .033), KMT2C (1.6% vs. 0%, p = .031), KMT2D (3.8% vs. 0.7%, p = .005), and SETD2 (3.2% vs. 0.9%, p = .039; Fig. 3; Table 2). Interestingly, when we excluded MSI‐H and POLE‐mutated specimens from the analysis, only MITF (1.9% vs. 0.0%, p = .007) and NF1 (2.9% vs. 0.3%, p = .013) remained significant.

Tumor Mutational Burden and Microsatellite Instability via NGS

TMB‐high (≥17 mutations/Mb) was observed more frequently in tumors of the younger patient cohort (9.7% vs. 2.8%, p < .001; Table 3). Moreover, when analyzed by NGS, there was a significantly higher rate of MSI‐H in the cohort of younger left‐sided CRCs (8.1% vs. 1.9%, p = .009). Interestingly, when analyzed by FA, there was no significant difference in the frequency of MSI‐H between younger and older patients, although a trend toward higher rates of MSI‐H was observed in younger patients (4.2% vs. 1.8%, p = .085; Table 3).

Table 3. Tumor mutational burden and microsatellite instability analysis between younger and older cohort.

image

Open in a new tab

Abbreviations: FA, fragment analysis; LCC, left‐sided colorectal cancer; MSI, microsatellite instability; NGS, next‐generation sequencing; TMB, tumor mutational burden.

Protein Expression and Gene Amplification

As we observed a higher mutation rate in MSH2 and MSH6 via NGS in tumors of younger compared with older individuals, a lower expression of MSH2 (4.2% vs. 0.5%, p < .001) and MSH6 (4.2% vs. 1.0%, p = .001) in younger compared with older patients was seen by IHC.

The other proteins involved in mismatch repair (i.e., MLH1 and PMS2) showed almost identical protein expression in the two groups (Table 4; supplemental online Fig. 1).

Table 4. Mismatch repair protein expression by immunohistochemistry.

image

Open in a new tab
a

Percentages reflect lacking the protein.

b

Significant differences in protein expression between younger and older LCC patients.

Abbreviation: LCC, left‐sided colorectal cancer.

Furthermore, ERBB2 was amplified at a higher frequency in younger patients compared with older patients (5.7% vs. 2.4%), although the difference was not statistically significant (p = .082). One patient in the younger cohort exhibited MET amplification (1.3%), whereas no patients in the older cohort showed MET amplification (0.0%); however, no significant difference was detected (p = .156; supplemental online Table 1).

Interrelationship Between MSI‐H, TMB‐High, BRAF Mutation, and PD‐L1

We further investigated whether there is a difference in BRAF mutation rate in MSI‐H tumors from younger versus older patients. Unfortunately, only a few patients in our database (n = 40) had data for both MSI‐H and BRAF mutations, and in those who did, there was no significant difference in BRAF mutation rate (9.1% vs 20%; supplemental online Table 2). The interrelationship between MSI‐H, TMB‐high, BRAF mutations, and programmed death‐ligand 1 (PD‐L1) expression was studied, and there were no statistically significant differences between younger and older patient cohorts (supplemental online Fig. 2).

Discussion

Increasing rates of CRC among young adults poses a global health issue and an incredible burden on patients, families, and health care providers. This rise in early‐onset CRC is primarily driven by distal tumors, yet both the etiology and risk factors remain unknown. Obesity and its associated behaviors, such as unhealthy dietary patterns and sedentary lifestyles, as well as gut microbiota [27] may play a crucial role in CRC risk for young adults. However, from a molecular perspective, much remains unknown. In addition, the lack of a global consensus on the age cutoff to define younger patients makes any comparison a challenge.

Herein, we demonstrated that younger patients with left‐sided CRCs exhibit a molecular profile that is different from that of left‐sided CRCs from older patients. Accordingly, younger patients have a higher TMB‐high and a greater MSI‐H rate.

Patients with MSI‐H or dMMR mCRC can now be given pembrolizumab (Keytruda; Merck & Co., Inc., Kenilworth, NJ) [28] and nivolumab (Opdivo; Bristol‐Myers Squibb, New York City, NY) [29] owing to recent U.S. Food and Drug Administration (FDA) approval of these two immune checkpoint inhibitors in this setting. Therefore, the findings reported in this current paper may have direct impact on treatment choices for younger patients.

We found significantly higher MSH6 and MSH2 mutation rates by NGS and significantly lower protein expression via IHC in younger compared with older patients (Fig. 3; Tables 2 and 4). Mutations that occur in MSH6 and MSH2 are found to be responsible for dMMR. In sporadic CRC, promoter hypermethylation of MLH1 is responsible for 80%–90% of MSI‐H cases, and isolated loss of MSH2 or MSH6 proteins, seen by IHC, has high specificity for a germline mutation in these genes [30]. Accordingly, we found that MSI‐H status was more frequent in left‐sided CRC specimens from younger patients than left‐sided CRCs from older patients via NGS analysis, and although FA showed the same trend, frequency differences did not reach statistical significance (Table 3). Although it is well established that dMMR can be accurately measured by directly enumerating known MSI loci using targeted deep sequencing (MSI‐NGS) [31] or by TMB [32], our results warrant some caution, and further validation is needed to elucidate this aspect. However, our findings are in accordance with previous studies that showed that MSI‐H occurs more frequently in younger patients, although frequencies vary widely [33], [34], and that the pattern of mutations leading to MSI‐H in younger patients is different from older patients [35], [36]. In fact, currently, we are examining whether mutations in specific MMR genes have a different impact on immune‐related biomarker expression (e.g., PD‐L1 overexpression and TMB level).

Our study confirms previous observations suggesting a higher rate of POLE mutations in younger patients, although in our cohort, only 1.6% of patients aged ≤45 years harbored POLE mutations, whereas 9.8% were detected in a prior study [8]. Recently, in 4,500 stage II/III CRCs, Domingo et al. [37] showed that POLE mutations are mutually exclusive with dMMR. They occur in 1% of patients, are characterized by an excellent prognosis, and are more frequent in younger adult at diagnosis.

MSI‐H status and POLE mutations, whether germline or somatic, lead to a hypermutated cancer phenotype [38], [39]. It is now well established that hypermutational status causes an enrichment of neoepitopes, which in turn can be recognized by the immune system and eventually lead to a potent cytotoxic T‐cell response. Accordingly, we showed that younger patients displayed a TMB‐high rate (defined as ≥17 mutations/Mb) threefold more frequently than older patients (9.7% vs. 2.8%, p < .001), probably owing to mutations in MSH6, MSH2, and POLE; in a prior study, we have shown a high correlation between TMB‐high and MSI‐H across several gastrointestinal cancers [40]. It is noteworthy that TMB‐high status is an emerging biomarker for response to immunotherapy [41], [42] and prognosis [43]. Of note, the observed increased rates of MSH2 and MSH6 and increased rates of MSI and TMB could be due to the increased proportion of younger CRC patients with hereditary conditions (e.g., Lynch syndrome).

Our findings suggest that left‐sided CRCs from younger patients more frequently harbor somatic mutations in genes that are associated with different cancer syndromes. As such, younger patients may have a higher risk of developing specific types of cancer as part of a hereditary cancer syndrome if these mutations represent germline mutations, including CRC. Germline mutations in MSH2 and MSH6 are associated with Lynch syndrome (also known as HNPCC); NF1 with NF1; PTEN with PHTS; TSC1 and TSC2 with TSC, SMAD4 with juvenile polyposis syndrome, and BRCA2 with HBOC. Unfortunately, we could not evaluate whether these mutations were germline, which is a limitation of our study. However, the strong correlation between these mutations with specific and well‐known hereditary syndromes underlines the importance of genetic counseling and screening in patients with early‐onset CRC.

Interestingly, in the current study, the genes that showed significantly different mutation rates between younger and older patients, although not associated with any known cancer syndrome, can be grouped together because of their function: KDM5C, KMT2A/2C/2D, SETD2, and CDC73 are histone methyltransferases or demethylases. Disruption of epigenetic regulation in CRC, namely DNA and histone methylation and demethylation, have gained attention in recent years, because it is now believed that these enzymes play a crucial role in the development of CRC [44]. Indeed, epigenetic modifications provide promising new targets for anticancer therapy, and several DNA methyltransferases and histone deacetylases inhibitors are already FDA‐approved anticancer drugs in hematologic malignancies (e.g., azacitidine, decitabine, vorinostat, romidepsin, and belinostat). For these reasons, numerous phase I/II trails are ongoing to test the safety and the efficacy of specific drugs that target histone modifiers in solid tumors, including CRC [45].

Of special interest, we found higher BRCA2 mutation rates in younger compared with older left‐sided CRC patients. BRCA2 germline mutant tumors have been shown to benefit from Poly (ADP‐ribose) polymerase (PARP)‐inhibitor therapy, as recently demonstrated by Mirza et al. [46]. Additionally, ERBB2 (HER2) amplification was observed at a higher rate in younger patients (5.7%) compared with older patients (2.4%), although the difference was not significant (p = .144). HER2 has been shown to be a promising predictive marker of response to anti‐HER2 therapy (i.e., HERACLES trial [47]). Therefore, these findings could lead to additional tailored therapies for this population of patients.

We acknowledge that our study has several limitations, such as the retrospective nature of the analysis, heterogeneous population, and the lack of clinical data that did not allow us to correlate these findings with outcomes. Therefore, future validations of these findings in prospective and larger cohorts are needed.

Conclusion

This is the first study to investigate the molecular differences between younger (≤45 years) and older adults (≥65 years) affected by left‐sided CRC. We have shown that molecular differences between younger and older patients are predominantly due to mutations in genes that are strongly associated with cancer‐predisposing syndromes, underlining the importance of genetic counseling and screening in this population of CRC patients. MSI‐H and TMB‐high tumors occur more frequently in younger patients, which may have a direct impact on clinical practice, as pembrolizumab and nivolumab are now FDA approved for the treatment of MSI‐H or dMMR mCRC patients. In addition, younger patients harboring ERBB2 (HER2) amplification could benefit from HER2‐targeted combination therapy, whereas BRCA2 mutant tumors may benefit from PARP‐inhibitor therapy. Finally, higher mutation rates in histone methyltransferases and demethylases occur in younger individuals and could therefore present new promising therapeutic targets.

Although the differences in tumor biology observed between younger and older patients with left‐sided CRCs warrant further validating studies, molecular tumor profiling in early‐onset CRC should be considered in order to allow exploration of novel therapeutic options. In addition, this analysis provides new insights into mutations that may guide development of novel tailored therapy in younger CRC patients. With confirmatory and prospective studies, these initial findings may influence our approach to younger adults with CRC in the future.

See http://www.TheOncologist.com for supplemental material available online.

Author Contributions

Conception/design: Alberto Puccini, Mohamed E. Salem

Provision of study material or patients: Alberto Puccini, Heinz‐Josef Lenz, John L. Marshall, David Arguello, Derek Raghavan, W. Michael Korn, Benjamin A. Weinberg, Kelsey Poorman, Arielle L. Heeke, Philip A. Philip, Anthony F. Shields, Richard M. Goldberg, Mohamed E. Salem

Collection and/or assembly of data: Alberto Puccini, David Arguello, Mohamed E. Salem

Data analysis and interpretation: Alberto Puccini, Heinz‐Josef Lenz, John L. Marshall, David Arguello, Derek Raghavan, W. Michael Korn, Benjamin A. Weinberg, Kelsey Poorman, Arielle L. Heeke, Philip A. Philip, Anthony F. Shields, Richard M. Goldberg, Mohamed E. Salem

Manuscript writing: Alberto Puccini, Heinz‐Josef Lenz, John L. Marshall, David Arguello, Derek Raghavan, W. Michael Korn, Benjamin A. Weinberg, Kelsey Poorman, Arielle L. Heeke, Philip A. Philip, Anthony F. Shields, Richard M. Goldberg, Mohamed E. Salem

Final approval of manuscript: Alberto Puccini, Heinz‐Josef Lenz, John L. Marshall, David Arguello, Derek Raghavan, W. Michael Korn, Benjamin A. Weinberg, Kelsey Poorman, Arielle L. Heeke, Philip A. Philip, Anthony F. Shields, Richard M. Goldberg, Mohamed E. Salem

Disclosures

Heinz‐Josef Lenz: Roche, Merck Serono, Bayer, Bristol‐Myers Squibb, Boehringer Ingelheim, Takeda (SAB), Merck Serono, Bayer (C/A); John L. Marshall: Caris Life Sciences (RF, H, SAB); David Arguello: Caris Life Sciences (E); Derek Raghavan: Caris Life Sciences (C/A); W. Michael Korn: Caris Life Sciences (E, OI), Merck, Eli Lilly and Company (SAB); Kelsey Poorman: Caris Life Sciences (E); Anthony F. Shields: Caris Life Sciences (RF, SAB). The other authors indicated no financial relationships.

(C/A) Consulting/advisory relationship; (RF) Research funding; (E) Employment; (ET) Expert testimony; (H) Honoraria received; (OI) Ownership interests; (IP) Intellectual property rights/inventor/patent holder; (SAB) Scientific advisory board

References

  • 1. Ferlay J, Soerjomataram I, Dikshit R et al. Cancer incidence and mortality worldwide: Sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer 2015;136:E359–E386. [DOI] [PubMed] [Google Scholar]
  • 2. Siegel RL, Miller KD, Fedewa SA et al. Colorectal cancer statistics, 2017. CA Cancer J Clin 2017;67:177–193. [DOI] [PubMed] [Google Scholar]
  • 3. Bailey CE, Hu CY, You YN et al. Increasing disparities in the age‐related incidences of colon and rectal cancers in the United States, 1975–2010. JAMA Surg 2015;150:17–22. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4. Weinberg BA, Marshall JL, Salem ME. The growing challenge of young adults with colorectal cancer. Oncology (Williston Park) 2017;31:381–389. [PubMed] [Google Scholar]
  • 5. Ballester V, Rashtak S, Boardman L. Clinical and molecular features of young‐onset colorectal cancer. World J Gastroenterol 2016;22:1736–1744. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6. Stigliano V, Sanchez‐Mete L, Martayan A et al. Early‐onset colorectal cancer: A sporadic or inherited disease? World J Gastroenterol 2014;20:12420–12430. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7. Vatandoust S, Price TJ, Ullah S et al. Metastatic colorectal cancer in young adults: A study from the South Australian population‐based registry. Clin Colorectal Cancer 2016;15:32–36. [DOI] [PubMed] [Google Scholar]
  • 8. Kothari N, Teer JK, Abbott AM et al. Increased incidence of FBXW7 and POLE proofreading domain mutations in young adult colorectal cancers. Cancer 2016;122:2828–2835. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9. Magnani G, Furlan D, Sahnane N et al. Molecular features and methylation status in early onset (</=40 years) colorectal cancer: A population based, case‐control study. Gastroenterol Res Pract 2015;2015:132190. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10. Antelo M, Balaguer F, Shia J et al. A high degree of LINE‐1 hypomethylation is a unique feature of early‐onset colorectal cancer. PLoS One 2012;7:e45357. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11. Ahnen DJ, Wade SW, Jones WF et al. The increasing incidence of young‐onset colorectal cancer: A call to action. Mayo Clin Proc 2014;89:216–224. [DOI] [PubMed] [Google Scholar]
  • 12. Silla IO, Rueda D, Rodriguez Y et al. Early‐onset colorectal cancer: A separate subset of colorectal cancer. World J Gastroenterol 2014;20:17288–17296. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13. Pearlman R, Frankel WL, Swanson B et al. Prevalence and spectrum of germline cancer susceptibility gene mutations among patients with early‐onset colorectal cancer. JAMA Oncol 2017;3:464–471. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14. Fidler MM, Gupta S, Soerjomataram I et al. Cancer incidence and mortality among young adults aged 20–39 years worldwide in 2012: A population‐based study. Lancet Oncol 2017;18:1579–1589. [DOI] [PubMed] [Google Scholar]
  • 15. Ben‐Ishay O, Brauner E, Peled Z et al. Diagnosis of colon cancer differs in younger versus older patients despite similar complaints. Isr Med Assoc J 2013;15:284–287. [PubMed] [Google Scholar]
  • 16. Wang R, Wang MJ, Ping J. Clinicopathological features and survival outcomes of colorectal cancer in young versus elderly: A population‐based cohort study of SEER 9 registries data (1988–2011). Medicine (Baltimore) 2015;94:e1402. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17. Li Q, Zhuo C, Cai G et al. Pathological features and survival outcomes of young patients with operable colon cancer: Are they homogeneous? PLoS One 2014;9:e102004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18. Heeke AC, Xiu J, Reddy SK et al. Molecular characterization of colorectal tumors in young patients compared with older patients and impact on outcome. J Clin Oncol 2016;34(suppl 4):505a. [Google Scholar]
  • 19. Abdelsattar ZM, Wong SL, Regenbogen SE et al. Colorectal cancer outcomes and treatment patterns in patients too young for average‐risk screening. Cancer 2016;122:929–934. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20. Siegel RL, Fedewa SA, Anderson WF et al. Colorectal cancer incidence patterns in the United States, 1974. ‐2013 J Natl Cancer Inst 2017;109. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21. Brule SY, Jonker DJ, Karapetis CS et al. Location of colon cancer (right‐sided versus left‐sided) as a prognostic factor and a predictor of benefit from cetuximab in NCIC CO.17. Eur J Cancer 2015;51:1405–1414. [DOI] [PubMed] [Google Scholar]
  • 22. Loupakis F, Yang D, Yau L et al. Primary tumor location as a prognostic factor in metastatic colorectal cancer. J Natl Cancer Inst 2015;107. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23. Petrelli F, Tomasello G, Borgonovo K et al. Prognostic survival associated with left‐sided vs right‐sided colon cancer: A systematic review and meta‐analysis. JAMA Oncol 2016. [Epub ahead of print]. [DOI] [PubMed] [Google Scholar]
  • 24. Tejpar S, Stintzing S, Ciardiello F et al. Prognostic and predictive relevance of primary tumor location in patients with RAS wild‐type metastatic colorectal cancer: Retrospective analyses of the CRYSTAL and FIRE‐3 trials. JAMA Oncol 2016. [Epub ahead of print]. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25. Arnold D, Lueza B, Douillard JY et al. Prognostic and predictive value of primary tumour side in patients with RAS wild‐type metastatic colorectal cancer treated with chemotherapy and EGFR directed antibodies in six randomized trials. Ann Oncol 2017;28:1713–1729. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26. Salem ME, Weinberg BA, Xiu J et al. Comparative molecular analyses of left‐sided colon, right‐sided colon, and rectal cancers. Oncotarget 2017;8:86356–86368. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27. Brennan CA, Garrett WS. Gut microbiota, inflammation, and colorectal cancer. Annu Rev Microbiol 2016;70:395–411. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28. Le DT, Durham JN, Smith KN et al. Mismatch repair deficiency predicts response of solid tumors to PD‐1 blockade. Science 2017;357:409–413. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29. Overman MJ, McDermott R, Leach JL et al. Nivolumab in patients with metastatic DNA mismatch repair‐deficient or microsatellite instability‐high colorectal cancer (CheckMate 142): An open‐label, multicentre, phase 2 study. Lancet Oncol 2017;18:1182–1191. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30. Kawakami H, Zaanan A, Sinicrope FA. Microsatellite instability testing and its role in the management of colorectal cancer. Curr Treat Options Oncol 2015;16:30. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31. Chalmers ZR, Connelly CF, Fabrizio D et al. Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden. Genome Med 2017;9:34. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32. Stadler ZK, Battaglin F, Middha S et al. Reliable detection of mismatch repair deficiency in colorectal cancers using mutational load in next‐generation sequencing panels. J Clin Oncol 2016;34:2141–2147. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33. Gryfe R, Kim H, Hsieh ET et al. Tumor microsatellite instability and clinical outcome in young patients with colorectal cancer. N Engl J Med 2000;342:69–77. [DOI] [PubMed] [Google Scholar]
  • 34. Farrington SM, McKinley AJ, Carothers AD et al. Evidence for an age‐related influence of microsatellite instability on colorectal cancer survival. Int J Cancer 2002;98:844–850. [DOI] [PubMed] [Google Scholar]
  • 35. Goel A, Nagasaka T, Spiegel J et al. Low frequency of Lynch syndrome among young patients with non‐familial colorectal cancer. Clin Gastroenterol Hepatol 2010;8:966–971. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36. Khan SA, Morris M, Idrees K et al. Colorectal cancer in the very young: A comparative study of tumor markers, pathology and survival in early onset and adult onset patients. J Pediatr Surg 2016;51:1812–1817. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37. Domingo E, Freeman‐Mills L, Rayner E et al. Somatic POLE proofreading domain mutation, immune response, and prognosis in colorectal cancer: A retrospective, pooled biomarker study. Lancet Gastroenterol Hepatol 2016;1:207–216. [DOI] [PubMed] [Google Scholar]
  • 38. Briggs S, Tomlinson I. Germline and somatic polymerase epsilon and delta mutations define a new class of hypermutated colorectal and endometrial cancers. J Pathol 2013;230:148–153. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Cancer Genome Atlas Network . Comprehensive molecular characterization of human colon and rectal cancer. Nature 2012;487:330–337. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40. Salem ME, Puccini A, Grothey A et al. Landscape of tumor mutation load, mismatch repair deficiency, and PD‐L1 expression in a large patient cohort of gastrointestinal cancers. Mol Cancer Res 2018;16:805–812. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41. Rizvi NA, Hellmann MD, Snyder A et al. Cancer immunology. Mutational landscape determines sensitivity to PD‐1 blockade in non‐small cell lung cancer. Science 2015;348:124–128. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42. Goodman AM, Kato S, Bazhenova L et al. Tumor mutational burden as an independent predictor of response to immunotherapy in diverse cancers. Mol Cancer Ther 2017;16:2598–2608. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43. Innocenti F, Ou FS, Zemla T et al. Somatic DNA mutations, MSI status, mutational load (ML): Association with overall survival (OS) in patients (pts) with metastatic colorectal cancer (mCRC) of CALGB/SWOG 80405 (Alliance). J Clin Oncol 2017;35(suppl 15):3504a. [Google Scholar]
  • 44. Gargalionis AN, Piperi C, Adamopoulos C et al. Histone modifications as a pathogenic mechanism of colorectal tumorigenesis. Int J Biochem Cell Biol 2012;44:1276–1289. [DOI] [PubMed] [Google Scholar]
  • 45. Huang T, Lin C, Zhong LL et al. Targeting histone methylation for colorectal cancer. Therap Adv Gastroenterol 2017;10:114–131. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46. Mirza MR, Monk BJ, Herrstedt J et al. Niraparib maintenance therapy in platinum‐sensitive, recurrent ovarian cancer. N Engl J Med 2016;375:2154–2164. [DOI] [PubMed] [Google Scholar]
  • 47. Sartore‐Bianchi A, Trusolino L, Martino C et al. Dual‐targeted therapy with trastuzumab and lapatinib in treatment‐refractory, KRAS codon 12/13 wild‐type, HER2‐positive metastatic colorectal cancer (HERACLES): A proof‐of‐concept, multicentre, open‐label, phase 2 trial. Lancet Oncol 2016;17:738–746. [DOI] [PubMed] [Google Scholar]

Articles from The Oncologist are provided here courtesy of Oxford University Press

RESOURCES