Mutations in PTEN activate the phosphoinositide 3-kinase (PI3K) signalling network, leading to many of the characteristic phenotypic changes of cancer. However, the primary effects of this gene on oncogenesis through control of the PI3K–AKT–mammalian target of rapamycin (mTOR) pathway might not be the only avenue by which PTEN affects tumour progression. PTEN has been shown to regulate the antiviral interferon network and thus alter how cancer cells communicate with and are targeted by immune cells. An active, T cell-infiltrated microenvironment is critical for immunotherapy success, which is also influenced by mutations in DNA damage repair pathways and the overall mutational burden of the tumour. As PTEN has a role in the maintenance of genomic integrity, it is likely that a loss of PTEN affects the immune response at two different levels and might therefore be instrumental in mediating failed responses to immunotherapy. In this review, we summarise findings that demonstrate how the loss of PTEN function elicits specific changes in the immune response in several types of cancer. We also discuss ongoing clinical trials that illustrate the potential utility of PTEN as a predictive biomarker for immune checkpoint blockade therapies.

A challenging task when more than one HLA gene is evaluated together by second-generation sequencing is to achieve a reliable read mapping. The polymorphic and repetitive nature of HLA genes might bias the read mapping process, usually underestimating variability at very polymorphic segments, or overestimating variability at some segments. To overcome this issue we developed hla-mapper, which takes into account HLA sequences derived from the IPD-IMGT/HLA database and unpublished HLA sequences to apply a scoring system. This comprehends the evaluation of each read pair, addressing them to the most likely HLA gene they were derived from. Hla-mapper provides a reliable map of HLA sequences, allowing accurate downstream analysis such as variant calling, haplotype inference, and allele typing. Moreover, hla-mapper supports whole genome, exome, and targeted sequencing data. To assess the software performance in comparison with traditional mapping algorithms, we used three different simulated datasets to compare the results obtained with hla-mapper, BWA MEM, and Bowtie2. Overall, hla-mapper presented a superior performance, mainly for the classical HLA class I genes, minimizing wrong mapping and cross-mapping that are typically observed when using BWA MEM or Bowtie2 with a single reference genome.

The non-classical human leukocyte antigen (HLA) class I genes present a very low rate of variation. So far, only 10 HLA-E alleles encoding three proteins have been described, but only two are frequently found in worldwide populations. Because of its historical background, Brazilians are very suitable for population genetic studies. Therefore, 104 bone marrow donors from Brazil were evaluated for HLA-E exons 1-4. Seven variation sites were found, including two known single nucleotide polymorphisms (SNPs) at positions +424 and +756 and five new SNPs at positions +170 (intron 1), +1294 (intron 3), +1625, +1645 and +1857 (exon 4). Haplotyping analysis did show eight haplotypes, three of them known as E*01:01:01, E*01:03:01 and E*01:03:02:01 and five HLA-E new alleles that carry the new variation sites. The HLA-E*01:01:01 allele was the predominant haplotype (62.50%), followed by E*01:03:02:01 (24.52%). Selective neutrality tests have disclosed an interesting pattern of selective pressures in which balancing selection is probably shaping allele frequency distributions at an SNP at exon 3 (codon 107), sequence diversity at exon 4 and the non-coding regions is facing significant purifying pressure. Even in an admixed population such as the Brazilian one, the HLA-E locus is very conserved, presenting few polymorphic SNPs in the coding region.

Human Leucocyte Antigen F (HLA-F) is a non-classical HLA class I gene distinguished from its classical counterparts by low allelic polymorphism and distinctive expression patterns. Its exact function remains unknown. It is believed that HLA-F has tolerogenic and immune modulatory properties. Currently, there is little information regarding the HLA-F allelic variation among human populations and the available studies have evaluated only a fraction of the HLA-F gene segment and/or have searched for known alleles only. Here we present a strategy to evaluate the complete HLA-F variability including its 5' upstream, coding and 3' downstream segments by using massively parallel sequencing procedures. HLA-F variability was surveyed on 196 individuals from the Brazilian Southeast. The results indicate that the HLA-F gene is indeed conserved at the protein level, where thirty coding haplotypes or coding alleles were detected, encoding only four different HLA-F full-length protein molecules. Moreover, a same protein molecule is encoded by 82.45% of all coding alleles detected in this Brazilian population sample. However, the HLA-F nucleotide and haplotype variability is much higher than our current knowledge both in Brazilians and considering the 1000 Genomes Project data. This protein conservation is probably a consequence of the key role of HLA-F in the immune system physiology.

The immune checkpoint HLA-G prevents maternal rejection of the fetus and contributes in cancer invasion and acceptance of allografts. The 5’ and 3’ regulatory regions of the HLA-G gene are polymorphic and balancing selection probably maintains this variability. It is proposed that nucleotide variations may affect the level of HLA-G expression. To investigate this issue we aimed to analyze how haplotypes of the 3’ untranslated region (3’UTR) with highest worldwide frequencies, namely UTR-1, UTR-2, UTR-3, UTR-4, UTR-5, UTR-18 and UTR-7, impact the expression of a luciferase reporter gene in vitro. Experiments performed with the HLA-G positive cell lines JEG-3 (choricarcinoma) and FON (melanoma), and with the HLA-G negative cell lines M8 (melanoma) and U251MG (glioblastoma) showed that the HLA-G 3’UTR polymorphism influences the response to endogenous cellular factors and may vary according to the cell type. UTR-5 and UTR-7 impact the activity of luciferase the most whereas UTR-2, UTR-3, UTR-4, and UTR-18 have intermediate impact, and UTR-1 has the lowest impact. These results corroborate the previous associations between amounts of plasma sHLA-G levels and 3’UTR haplotypes in healthy individuals and reinforce that 3’UTR typing may be a predictor of the genetic predisposition of an individual to express different levels of HLA-G.

Considering that others 14-bp associations were inconclusive and that other variation sites observed at HLA-G 3'UTR exhibit a proven role on post-transcriptional regulation of HLA-G expression, the complete 3'UTR segment should be analyzed in terms of disease susceptibility, instead of a single polymorphism.

Purpose Although non-small cell lung cancer (NSCLC) remains a deadly disease, new predictive biomarkers have emerged to assist in managing the disease, of which one of the most promising is the programmed death‐ligand 1 (PD-L1). Each, PD-L1 variant seem to modulate the function of immune checkpoints differently and affect response to adjuvant treatment and outcome in NSCLC patients. We thus investigated the influence of these PD-L1 genetic variations in genetically admixed NSCLC tissue samples, and correlated these values with clinicopathological characteristics, including prognosis. Materials and Methods We evaluated PD-L1 non-coding genetic variants and protein expression in lung adenocarcinomas (ADC), squamous cell carcinomas (SqCC), and large cell carcinomas (LCC) in silico. Microarray paraffin blocks from 70 samples of ADC (N=33), SqCC (N=24), and LCC (N=13) were used to create PD-L1 multiplex immunofluorescence assays with a Cell Signaling E1L3N clone. Fifteen polymorphisms of the PD-L1 gene were investigated by targeted sequencing and evaluated in silico using dedicated tools. Results Although PD-L1 polymorphisms seemed not to interfere with protein expression, PD-L1 expression varied among different histological subtypes, as did clinical outcomes, with the rs4742098A>G, rs4143815G>C, and rs7041009G>A variants being associated with relapse ( P =0.01; P =0.05; P =0.02, respectively). The rs7041009 GG genotype showed a significant correlation with younger and alive patients compared to carriers of the A allele ( P =0.02 and P< 0.01, respectively). The Cox regression model showed that the rs7041009 GG genotype may influence OS ( P <0.01) as a co-dependent factor associated with radiotherapy and recurrence in NSCLC patients. Furthermore, the Kaplan–Meier survival curves showed that rs7041009 and rs4742098 might impact PPS in relapsed patients. In silico approaches identified the variants as benign. Conclusion PD-L1 non-coding variants play an important role in modulating immune checkpoint function and may be explored as immunotherapy biomarkers. We highlight the rs7041009 variant, which impacts OS and PPS in NSCLC patients.

HLA‐A is the second most polymorphic locus of the human leucocyte antigen (HLA) complex encoding a key molecule for antigen presentation and NK cell modulation. Many studies have evaluated HLA‐A variability in worldwide populations, focusing mainly on exons, but the regulatory segments have been poorly characterized. HLA‐A variability is particularly high in the segment encoding the peptide‐binding groove (exons 2 and 3), which is related to the antigen presentation function and the balancing selection in these segments. Here we evaluate the genetic diversity of the HLA‐A gene considering a continuous segment encompassing the extended promoter (1.5 kb upstream of the first translated ATG), all exons and introns, and the entire 3′ untranslated region, by using massively parallel sequencing. To achieve this goal, we used a freely available bioinformatics workflow that optimizes read mapping for HLA genes and defines complete sequences using either the phase among variable sites directly observed in sequencing data and probabilistic models. The HLA‐A variability detected in a highly admixed population sample from Brazil shows that the HLA‐A regulatory segments present few, but divergent sequences. The regulatory segments are in close association with the coding alleles. Both exons and introns are highly variable. Moreover, patterns of molecular diversity suggest that the promoter, in addition to the coding region, might be under the same selective pressure, but a different scenario arises when it comes to exon 4 and the 3′UTR segment.