Rationale and objectives
The study of gene expression in cancer is an exceptional complement to the study of somatic mutations since it is possible to identify specific genes or signaling pathways that are disrupted and that could point to novel drivers or mechanisms of oncogenesis. Gene expression studies can also be used as an independent confirmation of the relevance of a mutation. For example, mutations in an oncogene are expected to increase said gene’s expression. By observing elevated expression of the gene of interest or of its targets, we can infer a causality relation between the mutation and the elevated expression.
Bioinformatic tools for the analysis of gene expression allow us to explore pathways upregulated and specific target genes in the full dataset or in smaller groups of tumors with characteristics in common.
The objective of this section is to compare gene expression levels between BCCs and non-affected skin to identify the disrupted signaling pathways in BCC. Furthermore, we used this expression data to search for signs of Hh or Hippo pathway activation in order to validate the relevance of the identified MYCN and PTPN14 mutations in BCC.
155 of 299 6.1. Gene expression in BCC
In order to compare global gene expression between BCC tumors and non-affected skin, we performed RNA sequencing of sets of samples of these two groups and carried out gene ontology analysis on genes upregulated in BCC (see Materials and Methods). Pathway analysis identified several highly significantly upregulated pathways, including “Basal cell carcinoma” (P= 6.5x10-5), “Hedgehog signaling” (P= 1.2x10-3) and “p53 signaling” (P=
1.1x10-2, Table 8).
We then carried out a gene set enrichment analysis (GSEA) for the MYCN and YAP1 target genes (Zhang et al., 2009, Valentijn et al., 2012) and found that genes upregulated in BCC are significantly enriched in these gene sets (normalized enrichment score NES= 1.89, FDR=
<1x10-4 and NES=1.93, FDR= <1x10-4, respectively (Figure 44a,b).
Pathway
(Kegg pathways) P-value (Benjamini corrected)
Cell cycle 1.5x10-8
Pathways in cancer 4.7x10-8
ECM-receptor interaction 1.5x10-5
Basal cell carcinoma 6.5x10-5
Focal adhesion 3.6x10-4
Hedgehog signaling pathway 1.2x10-3
p53 signaling pathway 1.1x10-2
DNA replication 1.2x10-2
TGF-beta signaling pathway 4.3x10-2
Melanomagenesis 6.0x10-2
Table 8. KEGG signaling pathways significantly over-represented in the list of upregulated genes in BCC.
156 of 299
Most interestingly, the subsets of tumors with MYCN mutations/amplifications and with PTPN14 mutations showed stronger enrichment for the MYCN and YAP1 target genes (NES= 2.11, FDR= <1x10-4 and NES=2.30, FDR= <1x10-4), respectively (Figure 44c,d).
These observations are consistent with the expected effects of MYCN stabilization/amplification and YAP1 nuclear accumulation (caused by PTPN14 mutations) in the BCC transcriptome. Moreover, subsets of sporadic and Gorlin syndrome resistant tumors showed higher enrichment for MYCN (NES= 2.28, FDR= <1x10-4, NES= 1.18, FDR=
<1x10-4) and YAP1 (NES= 2.43, FDR= <1x10-4, NES= 2.60, FDR= <1x10-4) target genes than all samples and than treatment naïve samples (NES= 1.78, FDR= <1x10-4 and NES= 1.77, FDR= <1x10-4) respectively.
157 of 299
Figure 44. Target genes of MYCN and YAP1 are upregulated in BCC. Enrichment of MYCN (a) and YAP1(b) targets among the genes upregulated in full BCC dataset when compared to skin and of MYCN in MYCN-mutated samples (c) or of YAP1 in PTPN14-mutated samples (d) by GSEA analysis. Genes were sorted according to their expression fold change between BCC and normal adjacent skin samples (x axis, 0 showing the most upregulated gene). Black vertical bars show the position of the target genes in the ranked list. The enrichment scores (green line (0.6 – upper;
0.59- lower)) significantly deviate from zero at the beginning of the distribution, showing that target genes are not randomly distributed in the ranked list but enriched in the upregulated genes. P= FDR corrected p-value. NES = normalized enrichment score.
a
d c
b
158 of 299
159 of 299
DISCUSSION
160 of 299
161 of 299
The great advances in sequencing technologies that have appeared in recent years, allow the sequencing of large numbers of samples quickly, accurately, and at a fraction of the cost of just a few years ago, allowing an increase in projects requiring the sequencing of large numbers of samples. Furthermore, the considerable number of NGS studies carried out to date has prompted the development of multiple analytical tools for the study of NGS data. In the area of cancer research, the consortiums that were set up to study cancer genomics favored the development of high quality and specific tools, as well as fruitful collaborations and interesting exchanges of approaches that have propelled the field of cancer genomics forward.
In our study, the largest unbiased, genome-wide analysis of BCC to date, we aimed to understand the molecular and genetic mechanisms involved in this tumor’s development and progression using available and novel tools. We found that besides the known drivers of tumorigenesis (PTCH1, TP53, SMO, SUFU) other genes downstream of GLI in the Hh pathway as well as in additional, independent signaling pathways, are significantly mutated in BCC and may play a role in this tumor’s development or progression (Figure 45). Global transcriptome analysis of BCC and non-affected skin confirmed the relevance of the newly identified drivers. Furthermore, we observed a predominant UV-light mutational signature in BCC and compare it to that of melanoma, another UV-light induced skin cancer, finding discreet but important differences in mutational signatures between these two tumor types. We have also correlated the identified novel drivers to specific tumor phenotypes, such as histological subtype and response to pharmacological treatment. We found that in histological subtypes associated with higher risk of recurrence, some of the novel drivers (MYCN, PTPN14, PPP6C) are more common than in subtypes correlated with lower risk of recurrence. Tumors resistant to pharmacological treatment displayed the expected profile of enrichment in SMO mutations.
MYCN missense mutations are drivers of tumorigenesis
One of the interesting identified candidate driver genes is MYCN, located on chromosome 2p24.3 and a downstream target of the Hh pathway (Gustafson and Weiss, 2010). N-myc is known to be expressed in skin keratynocites in the same spatial and temporal pattern as Shh in mice, and it has been observed to be completely absent from the epidermis of Shh-/-
162 of 299
mice, suggesting its expression is Shh-dependent (Mill et al., 2005). The focal amplification of MYCN is a known oncogenic event in the Hh-driven tumors neuroblastoma and medulloblastoma (Brodeur et al., 1984, Swartling et al., 2010, Jones et al., 2012).
Interestingly, when MYCN copy number was studied in a collection of 273 BCCs with fluorescence in situ hybridization (FISH), it was found that only 17.5% of the tumors harbored copy number gain of this gene, even though 73% of them displayed substantial elevation of MYCN expression in expression arrays (Freier et al., 2006). This observation confirmed that MYCN copy gain is a mechanism involved in BCC but strongly suggested additional methods of MYCN upregulation.
Figure 45. Signaling pathways involved in BCC. Key affected pathways and genes. The frequency of somatic point mutations and SCNAs for each gene is shown in the right and left panel, respectively, under each gene name. Genes inactivated in BCC are shown in blue, genes activated in BCC are in red. The intensity of the color corresponds to the fraction of samples affected.
163 of 299
We have shown through in silico modeling and biochemical assays that the MYCN mutations identified in 30% of our cohort impair MYCN ubiquitylation, promoting its stabilization.
The mechanism of MYCN functioning in tumorigenesis through protein-stabilizing point mutations has not been described before, in spite of MYCN missense mutations being previously found in a small fraction of neuroblastomas and medulloblastomas (Pugh et al., 2013, Cosmic Database). The differences in the mechanisms through which tumorigenesis is promoted in medulloblastoma/neuroblastoma and BCC by MYCN, are probably due to the fact that BCCs are highly mutated tumors while neuroblastoma and medulloblastoma are not (Pugh et al., 2013, Jones et al., 2012) (See Results and Figure 26).
The Hippo signaling pathway is active in BCC
Another main finding of our study is the discovery of the tumor suppressor PTPN14 as a SMG by MutSigCV in BCC. Mutations in this gene were found in 23% of the sample set, and 61% of all mutations were truncating mutations, a profile compatible with that of a tumor suppressor gene. Furthermore, we show that PTPN14, a regulator of the Hippo pathway, affects the localization of YAP1 (effector of the Hippo pathway) when mutated. To do so, we carried out immunohistochemistry stainings against YAP1 in wt and mutant PTPN14 BCCs and found that the nuclear localization of YAP1 was clearly increased when PTPN14 was mutated (See Results and Figure 34c). Furthermore, inactivating missense or truncating mutations in the tumor suppressor LATS1, another regulator of the Hippo pathway and activator of YAP1, were found in 16% of the sequenced exomes (See Results and Figure 36a). The relevance of the most frequent LATS1 missense mutation p.R995C, identified as a SRM by TumOnc, was further explored with in silico modeling and it was found to severely affect protein structure and stability.
YAP1 amplifications have been identified in a fraction of medulloblastomas (Fernandez et al., 2009), and PTPN14 mutations were previously observed in some relapsed neuroblastomas (Schramm et al., 2015). The identification of PTPN14 and LATS1 mutations in our sample set, as well as the two findings of aberrant Hippo pathway activation in two additional Hh-driven tumors (Wang et al., 2015, Jones et al., 2012) further strengthen the PTPN14 and LATS1 relevance in BCC. The interplay of Hh and Hippo pathways in BCC
164 of 299
maintenance and/or progression is an interesting observation that may have clinical repercussions in Hh-driven tumors.
Field cancerization in BCC
When we studied clonal BCCs, two pairs of tumors 10-15 cm apart were found to share only a TP53 LoF somatic mutation but no other driver or passenger mutations (See Results and Figure 43). This observation suggests the TP53 mutation could have occurred in an early precursor during embryogenesis (Lupski, 2013) or are a consequence of field cancerization, the presence of pre-neoplastic genetic alterations in a tissue that provide an enhanced genetic background for subsequent mutations (Braakhuis et al., 2003). This phenomenon has been suggested to occur in sun exposed skin (Jonason et al., 1996, Klein et al., 2010) and could be important in the development of clonal BCCs such as the ones described in this study.
It is expected that skin exposed to sunlight has a mutational signature compatible with UV-light induced mutagenesis and contains areas of field cancerization, but this phenomenon had only been studied in specific genes until earlier this year. A report on the mutational signature of 74 genes involved in skin and other cancer types in phenotypically normal, sun-exposed skin, was published (Martincorena et al., 2015). The authors observed that indeed, the great majority of mutations have the expected UV-light signature, and they found six genes that were significantly mutated in non-affected skin, TP53 among them.
Furthermore, most of these genes had an excess of inactivating mutations and NOTCH1, one of the identified genes, was biallelically inactivated more often than expected, these two characteristics being consistent with field cancerization. The profile of mutated genes found in non-affected skin was similar to the cutaneous squamous cell carcinoma (cSCC) profile, but differed from that observed in melanoma and in BCC (12 exome-sequenced tumors from Jayaraman et al., 2014). The authors hypothesized that this is due to the small number of melanocytes and the absence of hair follicles in the skin used to carry out their experiments. It would be interesting to further study the phenomenon of field cancerization in BCC, as it is known to be a common occurrence in other epithelial cancers (Simple et al., 2015, Leemans et al., 2011). BCC also provides the unique opportunity of studying multiple
165 of 299
tumors from the same individual, and adjacent non-affected skin is accessible for sampling and therefore can be assayed as well for predisposing mutations.
GWAS studies on BCC
MYCN and CASP8, two of the novel BCC genes identified in this study, are in the close vicinity of two susceptibility loci in a recently carried-out genome-wide association study (GWAS) for BCC in 4,572 individuals with BCC and 266,358 controls from the Icelandic population (Stacey et al., 2015). The GWAS hits identified mapped to chromosome 2p24 and 2p33, in the intergenic region of MYCN and FAM49A and in the region of CASP8 and ALS2CR12 respectively, and were successfully replicated in independent populations. Both SNPs were within DNAseI hypersensibility sites and were located inside binding sites for several transcription factors in keratinocytes. Furthermore, the CASP8-ALS2CR12 SNP was correlated with an eQTL affecting the expression of specific splicing forms of CASP8 in blood and adipose tissue from the Emilsson et al. (2008) study and successfully replicated in sun-exposed skin data from the GTEx Consortium (2013). These observations further emphasize the relevance of MYCN and CASP8 as BCC drivers, strengthening the evidence presented in this study.
Our finding of KNSTRN (mutated in 4% of our samples) as a novel BCC driver gene has been confirmed by a recent report of targeted sequencing of this gene in a collection of BCC samples previously interrogated for PTCH1 and SMO mutations (Atwood et al., 2015b). Jaju et al. (2015) revealed that in this sample set, 10% of the BCCs had a KNSTRN mutation, confirming the relevance of the KNSTRN mutations previously found in cSCC and melanoma (Lee et al., 2014), in BCC tumors.
Management and diagnosis of BCC: The effects of our novel findings
The results presented in this thesis provide an improved understanding of the genetic mechanisms involved in BCC tumorigenesis, and they are also applicable to tumor management. Most BCCs are treatable with non-invasive, ambulatory procedures, even when they recur. When pharmacological treatment is necessary due to tumor size, location or metastasis, the majority of tumors respond well to therapy. With the already effective treatment options, it is improbable that the findings presented in this thesis will change the
166 of 299
overall management of BCC. They will however, be very useful in a per-tumor basis, as particular individuals would benefit from genetic profiling of their tumors to determine the best course of treatment when conventional drugs for BCC are ineffective or contraindicated. In the case of SMO inhibitors for example, the genetic profiling of a BCC could reveal a large fraction of tumor cells carrying a SMO mutation that confers resistance to vismodegib, or a MYCN mutation that activates Hh downstream of SMO. These two scenarios would limit the benefits of using vismodegib as primary treatment. Based on this observation, the clinician would develop an alternative treatment plan without subjecting the patient to the strong systemic side effects of vismodegib without any prospected benefits.
In addition, genetic characterization of BCC could be applied as a routine assay in pathology departments for diagnosis purposes. The preliminary results presented in this thesis, regarding the correlation between recurrence risk/histological subtype and driver mutations, show that genetic characterization is a suitable alternative to histological classification. Although BCC histological subtypes are easy to differentiate by trained pathologists, some ambiguous cases of mixed or highly undifferentiated tumors will greatly benefit from genetic profiling in order to assure the chosen management plan is indeed the most effective one.
Testing protocols for BCC based upon the findings of this thesis
The role of molecular genetics in clinical diagnostics settings has increased steadily over the last few years. Hospitals are acquiring instruments and training employees in their usage and on the interpretation of the generated data. Clinical expertise is increasingly being complemented with genetic testing and the biological and genetic features of tumors are now being considered alongside tumor histology when devising treatment plans.
However, the implementation of genetic tests is still underway in many hospitals and departments within; the most effective approaches for different cases and tumor types have not necessarily been established at the institutional level. Up until now, BCCs have not been routinely genetically profiled: in most studies that require mutational assessment of the tumors, Sanger sequencing or targeted HTS of the main drivers are the only tests considered.
167 of 299
Based on our additional BCC driver findings and the reduction in sequencing cost, we recommend the analysis of the 387 genes of the Cancer Panel, if not of the full exome by HTS in all tumors. The information obtained with this approach improves tumor classification and could drive clinical management in particular cases, as discussed above.
Because BCC is a non-aggressive and in most cases easy to manage tumor, the value of sequencing them routinely was not evident prior to this work. The results of this thesis and the conclusions reached based on them, promote the sequencing of the most aggressive and large tumors in order to establish informed treatment plans for the affected patients.
With the continual reduction in sequencing costs and the ongoing streamlining and automation of the preliminary analysis of HTS data, whole exome or even whole genome sequencing will become the recommended genetic test for all cancers, including BCC.
Suggested future work
Identification of additional BCC drivers
This study of the genetic profiling of BCC can be extended by increasing the number of sequenced samples, a factor that has been shown to be directly correlated to the discovery of driver genes. Although the methods used to identify genes involved in BCC development allowed us to find several novel candidates, an estimation of the power of our study calculated on www.tumorportal.org (Lawrence et al., 2014) envisions our discovery ability (using MutSigCV) to be limited to the observation of genes mutated in 20-25% of the sample set (Figure 46).
The projected values are indeed consistent with our findings using MutSigCV, that identified genes mutated in 22% or more of the samples in the dataset. By using complementary algorithms and approaches we were able to find relevant genes mutated in a much smaller fraction of tumors (see Results section).
Doubling the sample size increases the power of this study to identify genes mutated in at least 15% of the cohort with this algorithm. Due to the high mutation rate in BCC, an extremely large sample set of 6,000 tumors or more would be necessary to achieve the same power as other cancer studies concerned with tumors with lower mutation rates or
168 of 299
larger data sets. For example, breast cancer (90% power for genes in 2% of patients) with 900 samples, kidney clear cell carcinoma (90% power for genes in ~4% of patients) with 400 samples, and acute myeloid leukemia (90% power for genes in 5% of patients) with 200 samples, have approximated saturation with a relatively small sample set (Lawrence et al., 2014) when compared to BCC.
Histological subtypes and their particular mutational signature
Although we have been able to correlate specific BCC driver genes with recurrence risk (which is directly linked to histological subtypes, see Introduction and Results sections), this part of the study can be extended to a detailed analysis of the mutational profiles of specific subtypes. We have performed preliminary analyses of the correlation between histological subtype and driver mutational profile in BCCs, using the most representative histological subtype per tumor since most of the samples are of mixed histology (Sexton et al., 1990). The results are encouraging and we have found correlations between some subtypes and specific drivers for example, MYCN mutations are more common in morpheaform and metatypical tumors than in nodular or superficial (see Results section).
Figure 46. Number of samples needed to detect significantly mutated genes as a function of a tumor’s median mutation rate. The number of tumor-blood pairs needed to achieve 90%
power for 90% of the genes is represented in the y axis. Median background mutation frequency is depicted in the x axis. Values for BCC (based on this study) are in bold and highlighted with a black dotted line. The black dot indicates sample size of this study. The sample size is only adequate to observe genes mutated between 20-25% above background. Plot generated with www.tumorportal.org.
169 of 299
It is however necessary to increase our sample size to be able to carry out a complete
It is however necessary to increase our sample size to be able to carry out a complete